Certification from top AI Startups

Artificial Intelligence Course in Hyderabad with hands on project experience

Waste no time, grab the opportunity to learn core AI with the best artificial intelligence course in Hyderabad. Sign up for the 9 months program and learn from experts in live-interactive classes. Moreover, bring your own projects and get direct company certification. In addition, build your career strong under proper guidance with our artificial intelligence training.

CALL US NOW

1800-419-0840

350+

HOURS LIVE SESSIONS

15+

LIVE PROJECTS

3

INDUSTRY PROJECTS

Program Features of artificial intelligence course in Hyderabad

Direct Company certification

Bring your own projects and get proper assistance to complete it. Also, earn project certification from top startups.

Self design your courses

Most importantly, get the chance to build your own course to meet your learning requirements. Also, learn it under expert supervision.

Subscription and program access

Get a 3 year subscription access to the courses. In fact, even after course completion, you can come back and revise the modules!

Career support and referrals

Firstly, you get free career counseling and support. Secondly, we prepare you for interviews and furnish you with job referrals.

Certification from top AI Startups

Artificial Intelligence Course in Hyderabad with hands on project experience

Waste no time, grab the opportunity to learn core AI with the best artificial intelligence course in Hyderabad. Sign up for the 9 months program and learn from experts in live-interactive classes. Moreover, bring your own projects and get direct company certification. In addition, build your career strong under proper guidance with our artificial intelligence training.

CALL US NOW

1800-419-0840

350+

HOURS LIVE SESSIONS

15+

LIVE PROJECTS

3

INDUSTRY PROJECTS

LIFETIME

ACCESS OF COURSE

Program Features of artificial intelligence course in Hyderabad

Program Duration

9 months of faculty led live online classes by industry expert. 300+ hrs sessions with 15+ live industry projects.

3 Year subscription

Get yourself trained in live-interactive classes. In addition to this, get a 3-year subscription to access these courses too!

Build Your Own Course

Self-design your courses at Skillslash under expert supervision. Also, assemble your learning modules and get trained in live interactive classes.

Course Fees

INR. 89,000/- (+ 18% GST)
6 months NO-COST EMI on all major credit cards | *Interest free loan option

Guaranteed Job Referral

Sign up in our data science training and get certified by top AI startups. Further, we provide career support with guaranteed job referrals.

Project Experience Certification

Get Project experience certificate directly  from companies and showcase relevant experience in AI/ML domain.

A brief outline on the artificial intelligence course in Hyderabad

Hyderabad city is not just the city of pearls. But also, home for tech giants in the IT sector. Moreover, Hyderabad is flourishing with a booming economy, leading to more MNC’s in IT. For instance, Accenture, IBM and Cognizant.. Also, this explains the growing demands for higher education in the field of advanced computer science in the city. Thus, highlighting why an artificial intelligence course in Hyderabad is highly sought. ...
Further, getting an artificial intelligence training in Hyderabad is likely to boost individual portfolios. Especially, when it comes to getting first preference in hiring. Also, an artificial intelligence course in Hyderabad opens a plethora of job opportunities. Thereby, giving you the chance to don respectable and key positions in companies. In addition, the salary package after signing up for an artificial intelligence course is remarkably high.

Why choose Skillslash’s artificial intelligence course in Hyderabad over others?

At Skillslash’s artificial intelligence course in Hyderabad, special focus is given to industry training. In addition, you get the opportunity to associate with top startups and complete real-time projects in AI and ML. Moreover, all these expert training is available through live-interactive classes at affordable packages. Besides, you can self-design your courses and earn shareable certification.

What are the key requirements for enrolling in Skillslash’s artificial intelligence course in Hyderabad?

Firstly, Skillslash offers two important data science and ai, ml courses in Hyderabad. Say, the Full-Stack AI and ML Program and the Data Science and AI program. In which, the former focuses on professionals and the latter focuses on fresh graduates and college students. Most importantly, the program for professionals is specifically designed for those having 1 or more years of experience. In short, this experience can be either in the IT domain or non-IT domain. In addition, those who have a background in MCA, BCA or MBA are also given preference.

 

Next comes Skillslash’s artificial intelligence course in Hyderabad curated especially for college going students. This artificial intelligence training in Hyderabad is designed for those pursuing a graduation or post graduation in college. In general, a basic understanding of mathematics, programming and statistics is mandatory for enrolling in this artificial intelligence course in Hyderabad. Furthermore, even if you hail from a background foreign to data science or AI, you will get additional support to learn introductory modules.

What are the job prospects after completing an artificial intelligence course in Hyderabad?

In fact, there are many tech giants in Hyderabad actively looking for artificial intelligence job roles. Especially top-tier companies like Accenture, Cognizant and Deloitte. In addition, firms such as IBM and Infosys also hire for these roles. Besides, all these MNC’s offer bounteous salary packages. Since, there are extensive applications for AI, which is in fact spread over different domains, there is huge career scope. Therefore, enrolling in an artificial intelligence course in Hyderabad is the best decision you can make.

What are some of the important projects offered under Skillslash’s artificial intelligence course in Hyderabad?

Here, at Skillslash you can avail the opportunity to work in 15+ live industrial projects over different domains. Most importantly, you can bring your own projects at Skillslash and gain direct company certification on completion. For instance, we offer variety of projects such as – 

  • Telecom –  Predicting the behavior of customers for identifying the probability of churn off.
  • Sales and marketing – For prediction of closing deals.
  • Manufacturing – To predict the failure of machines for heavy machine predictive maintenance.

Why is an artificial intelligence course in Hyderabad highly sought?

Firstly, the completion of a best artificial intelligence course in Hyderabad opens the way for a lucrative career. Most importantly, with skilled expertise in artificial intelligence, you get to don several job hats. Besides, businesses nowadays are in the lookout for technically skilled personnel in artificial intelligence to boost company growth.

Most importantly, completion of an artificial intelligence course in Hyderabad enables you to perform vital tasks. Especially, when it comes to businesses with the prediction of future scope of events. 

Is there a demand for a data scientist and artificial intelligence engineer in 2021?

An artificial intelligence engineer, for example, develops new systems employing AI approaches that will be advantageous in the future. Furthermore, data science job roles consistently rank in the top three in every job demand report for the previous year. This also includes the prerequisites for artificial intelligence and machine learning specialists.

Most importantly, researchers all around the world predict that demand for these employment types will continue to grow in the future. Similarly, ai ml courses are bringing more people to the forefront of their careers. The job statistics, in particular, show that after completing an artificial intelligence course in Hyderabad, you will be on the radar of multinational corporations. In addition, you will also be offered a competitive remuneration package. As a result, a free online artificial intelligence course with certificates in India is in high demand right now.

What are the most significant employment roles that an artificial intelligence training in Hyderabad can lead to?

After earning a certification in an artificial intelligence course, you’ll have a better chance of moving up the corporate ladder. Furthermore, becoming certified in a machine learning or artificial intelligence course in Hyderabad opens up a myriad of work prospects. To begin with, there are a variety of roles that you can pursue in addition to that of an artificial intelligence engineer. Also, skills in SQL, data analysis, and data warehousing, for example, might pave the way to a job as a business analyst.

Aside from data science ideas, sophisticated statistics, and programming languages such as Python, SAS, and R can help you land a job as a data scientist. In addition, you also get to work as a statistician. Furthermore, an artificial intelligence course online certification can assist you in gaining a comprehensive understanding of signal processing methodologies, computer languages, and neural network structures. 

Besides, having a strong foundation in machine learning algorithms and models will help you acquire your dream machine learning engineer/scientist position. In summary, all of the aforementioned skills may be acquired by enrolling in an online data science or artificial intelligence course in Hyderabad.

What makes an artificial intelligence course in Hyderabad so important?

First and foremost, the area of data science is concerned with uncovering trends and patterns in both structured and unstructured data. Data science, in particular, encompasses AI and machine learning approaches. Machine learning is a subset of artificial intelligence, which has its own branches. In addition, taking an artificial intelligence course in Hyderabad is recommended. Especially, because AI offers a lot of promise when it comes to making the best judgments in even the most complex business settings. Besides, artificial intelligence, deep learning, and machine learning also play a significant role in predicting future business outcomes.

As a result, enrolling in ai ml courses in Hyderabad and becoming certified in them will help you improve your profile. Furthermore, the topic of machine learning paired with artificial intelligence is regarded as important for research since it enables people to harness the power of data, assisting organizations in customer acquisition, innovative analysis, future output forecasting, and strategic marketing. As a result, data science, AI, and machine learning applications span a wide range of domains, which explains the field’s breadth.

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Robots are not going to replace humans, they are going to make their jobs much more humane” 
Sabine Hauert, Co-founder of Robohub.org

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    Top-tier certification direct from companies

    Project experience certification with artificial intelligence course in Hyderabad

    Equip yourself to solve real-time problems by working with live projects. Besides, not just learn academic theory but get top-level industry experience.

    Earn industry experience

    In addition to learning core academic theory, get proper project experience. Also, gain certification from companies.

    Get placed in MNC’s

    Boost your portfolio by gaining relevant experience. Also, get proper career training to land in your dream roles.

    Spend less but reap more

    Study under the guidance of experts and get skilled

    You Invest

    89,000
    12hrs/week

    Course Curriculum - Artificial Intelligence Course in Hyderabad

    Milestone 0

    Get skilled in basics of programming

    Learn about the fundamentals of programming. Besides, this can aid candidates irrespective of their IT/Non-IT domains.

    Acquire skills in fundamentals of math

    Get basic knowledge about statistics, calculus and probability. Further, this helps in learning data science and AI easier.

    Learn the basics of domain and cloud

    Introduction to cloud followed by domain training. In fact, we will cover different domains such as manufacturing and healthcare.

    Students learning online Skillslash’s artificial intelligence course in Hyderabad
    Milestone 1

    Get in depth knowledge of python

    Acquire informative knowledge on python and analytics. For example, Pandas, Numpy, Seaborn and Matplotlib.

    Learn more about EDA, statistics and storytelling

    Work in multiple projects and get insights on Exploratory Data Analysis (EDA). In addition, learn in depth about statistics and probability.

    Projects and case studies

    Get involved in multiple case studies involving python and data analytics. Furthermore, work in 1 capstone project and gain experience.

    Skillslash’s collaborative and live interactive artificial intelligence training in Hyderabad
    Milestone 2

    Acquire knowledge on ML

    Study ML in depth. Especially machine learning algorithms. For instance, supervised and unsupervised learning techniques. Also, learn it alongside projects and case studies.

    Get knowledge about time series and modelling

    Learn more about python-based time series forecasting. Also, get hands on knowledge on advanced modelling techniques like model tuning and feature engineering.

    Guided capstone projects

    You get to work on capstone projects. In addition, you will learn more about cloud. Also, you will get domain training covering different domains like retail and healthcare.

    Milestone 3

    Know more about deep learning and computer vision

    Get advanced computer vision training alongside deep learning algorithms. Also, get hands on multiple case studies and a capstone project.

    Learn about Auto AI and NLP

    Know more about advanced text analytics and NLP. Also, using python NLTK library work on a chatbot project from the start.

    Study about model deployment and reinforcement learning

    Gain knowledge on reinforcement learning and model deployment using GCP and AWS.

    skillslash-course-milestone-3
    Milestone 4

    Preparation of resumes

    With Skillslash In addition to learning core data science and AI, get proper career training. Also, learn how to perfect your resumes to get first preference in the hiring process.

    Expert driven mock tests and interview guidance

    Get equipped to face interview questions hands on. Also, learn to answer vital interview questions by solving several mock tests.

    Job referrals

    Gain job referrals that makes getting placed in top startups as well as MNC’s easier.

    skillslash-milestone-4-hyderabad-course-AI-ML

    Reasons why you should sign up for the AI program

    Distinctive program features of artificial intelligence course in Hyderabad

    What makes Skillslash’s artificial intelligence training stand out?

    Project Certification

    Here, you get the opportunity to bring your own projects and complete it under expert guidance. Moreover, you can earn direct company certification for project experience. In addition, along with theory, you get to work on live industry projects with startups.

    Get placed in MNC’s

    At Skillslash you will receive expert level training. Moreover, the mentorship is such that you will be fully equipped to face interviews and clear them. Besides, you get career counseling and outcome driven learning tracks.

    Domain training

    You will be at the receiving end for elective tracks for industry and functional specialization. Furthermore, you will get domain training that helps career transition smoother. Especially, into the data science, AI or ML domain.

    Student Testimonials

    First-hand feedback for our artificial intelligence course in Hyderabad

    The merits of Skillslash’s artificial intelligence course in Hyderabad

    Hitting the the arrow in the career target with artificial intelligence training
    1. Learners can work on their own projects under our guidance to reap fruitful results.
    2. It is a more advanced version of the Project Certification for professionals with more than 10 years of experience. 
    3. You get a chance to experience live project training in an appropriate space.
    4. Decision makers in teams can use this as a way to get a POC done. In addition, find better resources to resolve project issues.
    A girl student in front of a laptop getting artificial intelligence training online
    1. Learn specialized courses emphasizing industry training. Moreover, benefit from instructor-led sessions.
    2. The platform lets you curate personalized learning tracks based on your career goals and experience.
    3. You can choose modules based on your learning preferences. Additionally, choose what resonates with you professionally. 
    4. The program covers a vast array of topics, allowing you to customize your own learning paths.
    Student writing down notes under Skillslash’s artificial intelligence course in Hyderabad
    1. Design eye-catching project portfolios. Also, apply the practical problem-solving skills to real-world situations. 
    2. In addition, obtain certifications from top-tier companies and make your portfolio outstanding.
    3. You can choose a project that is relevant to your domain preferences. Also, with shareable certificates gain interview preferences.
    4. For freshmen, we also offer internships with industry training.

    Course Details

    Chapter 1: Introduction to Programming ( 3 hrs )

    • What is a programming language ?
    • Source code Vs bytecode Vs machine code

    Also, learn about –

    • Compiler Vs Interpreter
    • C/C++, Java Vs Python

    Chapter 2: Jupyter notebook basics (1 hrs)

    • Different type of code editors in python
    • Introduction to Anaconda and jupyter notebook

    Chapter 3: Python Programming Basics (2 hrs ) 

    • Variable Vs identifiers
    • Strings Operators Vs operand

    And also,

    • Procedure oriented Vs modular programming

    Chapter 4: Statistics basics (4 hrs)

    • Introduction to statistics
    • Measures of Central Tendency

    Further, it covers –

    • Measures of dispersion
    • Inferential statistics and Sampling theory

    Chapter 5: Introduction to probability (4 hrs)

    • Introduction to probability
    • permutations and combinations

    Also, including –

    • Addition and Multiplication Rule
    • Conditional Probabilities

    Introduction to Programming

    • What is Programming Language?
    • Why do we need a Programming Language?

    In addition, it includes –

    • Different types of Programming Language
    • Why do we prefer to code in a High-Level Programming
      Language?

    Further, it covers –

    • What is Compiler? What is an Interpreter?
    • Compile Time vs Run Time

    Also, it contains –

    • Compile Time Error vs Run Time Error.

    Introduction to Python

    • What is Python?
    • Why do we need Python?

    Further, it includes –

    • Python is Compiled or Interpreted?
    • How a Python Program runs on our system?

    Besides, it has –

    • Features of Python
    • Memory Management in Python
    • Different Implementations of Python

    Conditional and Loops

    • Conditional Statement

    Use of “if”, “if-else”, “if-elif-else” statement

    • Loop Statement

    In addition, it covers –

    For loop

    When to use for loop

    For-else loop

    While Loop

    Besides, it has –

    When to use while loop

    While-else loop

    Also, covering –

    Infinite loop

    Break, Continue and Pass

    Python Programming Components

    • Writing your First Python Program
    • Linting Python code

    Also, it covers –

    • Formatting Python code
    • Understanding

    In addition, it has –

    • Few important function
    • Command Line Arguments

    Besides, it contains –

    • Python Operators

    Data Types in Python        

    • Fundamental Data Types
    • Strings
    • Numbers
    • None Type
    • Boolean Type

    Also, covering –

    • Derived Data Structure
    • Introduction to List

    Further, the module has –

    • List creation and importance of eval() while taking list as input
      from the user

    Also, it contains –

    • List comprehension
    • List properties and some basic operations

    Function

    • What is a function?
    • Function as a first-class citizen

    Further, the module contains –

    • What is the use of function? What is the DRY Principle?
    • How to define a function.

    Also, the module covers –

    • Function call vs Function referencing
    • What are inputs and outputs to the function?
    • Parameters vs Arguments
    • Types of Arguments

    Further, covering –

    • Return statement
    • Recursion
    • Namespace vs Scope
    • Anonymous Function and Lambda Expression

    Besides, the module has –

    • Filter, map, sort and reduce function
    • Closure Concept
    • Iterator Concept

    Exception Handling

    • What is an Exception?
    • Why do we need Exception Handling?

    Also, covering –

    • Type of Errors
    • Exception Handling Keywords

    Further, it has –

    • Nested try-except block
    • Default except for block
    • Try with multiple except block

    Modules in Python

    • What is Module?
    • Introduction to Modular Programming

    Also, it contains –

    • Module Search path
    • Importing Modules and different import statement

    Besides, it has –

    • Types of Modules
      • Builtin Modules
      • User Defined Modules
      • Package

    File Handling

    • What is File Handling?
    • Why do we need File Handling?

    And, also covering –

    • Type of Files
    • File Operation

    Regular Expression

    • What is Regular Expression?
    • Why do we need Regular Expression?

    Further, it contains –

    • Importing regex module
    • What is Raw string and why do we need it?

    Also, it covers –

    • Sample regex pattern and it’s interpretation
    • Important Methods

    Numpy in Python

    • What is Numpy?
    • Why is Numpy required?

    Also, the module has –

    • What is an array?
    • Why do we need an array when we have a list?
    • Array Operations
      • Creating array using numpy
      • Printing an array

    Further, it has –

    • Indexing and Slicing
    • Basic operations
    • Universal Functions

    In addition, the module covers –

    • Arrays with Structured Data
    • Changing shape of an array
    • Array Broadcasting
    • Vectorization

    Also, covering –

    • Iterating over an array
    • Splitting an array
    • View vs Copy

    Besides, the module has –

    • Vector Stacking
    • Miscellaneous Functions and Methods
    • Numpy and Scipy
    • Numpy and Pandas

    Visualization of Data in Python

    • Matplotlib
      • Lines and Markers
      • Figures and Axes

    Also, covering –

    • Figures and Subplots
    • Watermark
    • Shapes
    • Polygon and Arrows

    Further, the module has –

    • Beizer Curves
    • Curves
    • Annotations
    • Scales
    • Twin Axis

    And, also –

    • Boxplot and Violin Plots
    • Visualize Titanic Dataset with Box and Violin plots
    • Pie Charts
    • Stacked Plots
    • Color Maps
    • Autocorrelation

    Pandas in Python

    • What is Pandas?
    • Why do we need Pandas?
    • Numpy vs Pandas

    Also, covering –

    • Pandas Data Structure
    • Series
      • Creating Series
      • Indexing and Slicing operation
    • Data Frame
      • Creating Data Frame
      • Indexing and Selection in Data Frame

    Further, it covers –

    • Addition and Deletion of rows and Columns
    • Iterating over DataFrame

    Also, covering –

    • Reshaping Data Frame
    • Handling Missing Data in data Frame
    • Grouping Data Frame

    Besides, it has –

    • Sorting Data Frame
    • Stacking and Unstacking

    Also, along with –

    • Concatenating and Merging Data Frame
    • Pandas Time Series
    • Exporting Dataframe to CSV and Excel
    • EDA using Pandas

    Part 1 – Introduction to Probability theory and Statistical

    Inferences
    • Introduction to Probability Principles
    • Random Variables and Probability principles

    Further, the module covers –

    • Discrete Probability Distributions – Binomial , Poisson etc
    • Continuous Probability Distributions – Gaussian, Normal, etc
    • Joint and Conditional Probabilities

    Also, it covers –

    • Bayes theorem and its applications
    • Central Limit Theorem and Applications

    Part 2 – Statistics and Foundation

    • Elements of Descriptive Statistics
    • Measures of Central tendency and Dispersion

    Further, the module has –

    • Inferential Statistics fundamentals
    • Sampling theory and Scales of Measurement

    Also, covering –

    • Covariance and correlation

    Part 3 – Hypothesis Testing and its Applications

    • Basic Concepts – Formulation of Hypothesis , Making a decision
    • Advanced Concepts – Choice of Test – t test vs z test

    Besides, the module contains –

    • Evaluation of Test – P value and Critical Value approach
    • Confidence Intervals , Type 1 and 2 errors
    • Chi-squared and F tests

    Also, it covers –

    • Industry Applications – Two sample mean , A/B testing

    Part 4 – Exploratory Data Analysis and the Art of Storytelling

    • Ingest data
    • Data cleaning

    In addition, it has –

    • Outlier detection and treatment
    • Missing value imputation

    Further, covering –

    • Impact of Data Visualization
    • Univariate Analysis
    • Bivariate Analysis and ANOVA

    Also, it contains –

    • The science of Storytelling
    • Sliding like a management consultant

    Project – Exploratory analysis on Credit card data

    • Capstone Project for Business Analysis

    Part 0 – A primer on Machine Learning

    • Types of Learning – Supervised, Unsupervised and Reinforcement
    • Statistics vs Machine Learning

    Also, it contains –

    • Types of Analysis – Descriptive, Predictive, and Prescriptive
    • Bias Variance Tradeoff – Overfitting vs Underfitting

    Part 1 – Regression – Linear Regression

    • Correlation vs Causation
    • Simple and Multiple linear regression
    • Linear regression with Polynomial features

    Moreover, it contains –

    • What is linear in Linear Regression?
    • OLS Estimation and Gradient descent
    • Model Evaluation Metrics for regression problems – MAE , RMSE, MSE,
      and MAP

    Part 2- Classification – Logistic Regression

    • Introduction to Classification problems
    • Logistic Regression for Binary Problems
    • Maximum Likelihood estimation

    In addition, it has –

    • Data imbalance and redressal methodology
    • Upsampling, Downsampling and SMOTE

    In addition, it has –

    • one vs Rest (OVR) for multinormal classification.
    • Model Evaluation Metrics for classification-confusion matrix/
    • Misclassification error, Precision, Recall, F1 score, and AUC-ROC

    And, also –

    • Choosing the best error metric for a problem
    Part 3 - Clustering - K means
    • Introduction to Unsupervised Learning
    • Hierarchical and Non-Hierarchical techniques

    And also,

    • K Means Algorithms – Partition based model for clustering
    • Model Evaluation metrics – Clustering

    Part 4 – KNN

    • Introduction to KNNs
    • KNNs as a classifier
    • Non Parametric algorithms and Lazy learning ideology

    And also,

    • Applications in Missing value imputes and Balancing datasets

    Part 5 – Advanced Regression Models

    • Introduction to regularization
    • Ridge regression
    • Lasso regression

    Part 6 – Decision tree

    • Nonlinear models for classification
    • Intro to decision trees
    • Why are they called Greedy Algorithms

    In addition. It covers –

    • Information Theory – Measures of Impurity
    • Stopping criteria for trees
    • Susceptibility to overfitting and high variance

    And also,

    • Prevention of overfitting with Pruning or Truncation

    Part 7- Ensemble techniques

    • introduction to Bagging as an Ensemble technique
    • Bootstrap Aggregation and out of bag error

    Further, covering –

    • Random Forests and its Application in Feature selection
    • Scent and Boosting

    And also,

    • How Boosting overcomes the Bias – Variance Tradeoff

    Gradient Boosting and Xgboost as regularized boosting

    Part 8 - Support Vector Machines
    • Introduction to Expectation–Maximization Algorithms
    • The kernel trick
    • Linear, Polynomial, and RBF kernels and their use cases

    Further, it has –

    • SVMs for regression and classification
    • Applications in Multiclass classification

    Part 9 – Bayesian Family Algorithms and Intro to Text
    Classification

    • Naive Bayes for Text classification
    • Bag of words and TF-IDF algorithm
    • Multinomial and Gaussian Naive Bayes

    And, also –

    • Bayesian Belief networks and Path models

    Part 10 – Time-series Analysis

    • Intro to Time series and its decomposition
    • Autocorrelation and ACF/PACF plots
    • The Random Walk model and Stationarity of Time Series
    • Tests for Stationarity – ADF and Dickey-Fuller test
    • AR, MA, ARIMA, SARIMA models for univariate time series
      forecasting

    And, also –

    • A regression approach to time series forecasting
    Part 11 - How to Build and Deploy a Machine Learning pipeline
    • Loading data
    • Feature engineering techniques
    • Principal Component Analysis for Dimensionality reduction

    In addition, covering –

    • Linear Discriminant Analysis
    • Feature Selection Techniques – Forward and Backward
    • elimination, RFE

    Also, it contains-

    • Model Tuning and Selection
    • Deploying a Machine Learning Model
    • Serving the model via Rest API

    Part 12 – AutoML

    • Introduction to AutoML
    • Auto learn

    Also, covering –

    • TPOT models
    • Auto Keras

    Part 0 – A primer on Machine Learning

    • Types of Learning – Supervised, Unsupervised and Reinforcement
    • Statistics vs Machine Learning

    Also, it contains –

    • Types of Analysis – Descriptive, Predictive, and Prescriptive
    • Bias Variance Tradeoff – Overfitting vs Underfitting

    Part 1 – Regression – Linear Regression

    • Correlation vs Causation
    • Simple and Multiple linear regression
    • Linear regression with Polynomial features

    Moreover, it contains –

    • What is linear in Linear Regression?
    • OLS Estimation and Gradient descent

    Also, covering –

    • Model Evaluation Metrics for regression problems – MAE , RMSE, MSE,
      and MAP

    Part 2- Classification – Logistic Regression

    • Introduction to Classification problems
    • Logistic Regression for Binary Problems

    In addition, it covers –

    • Maximum Likelihood estimation

    Besides, it has –

    • Data imbalance and redressal methodology
    • Upsampling, Downsampling and SMOTE
    • one vs Rest (OVR) for multinormal classification.

    Further, the module has –

    • Model Evaluation Metrics for classification-confusion matrix/
    • Misclassification error, Precision, Recall, F1 score, and AUC-ROC

    And, also –

    • Choosing the best error metric for a problem

    Part 3 – Clustering – K means

    • Introduction to Unsupervised Learning
    • Hierarchical and Non-Hierarchical techniques
    • K Means Algorithms – Partition based model for clustering

    And also,

    • Model Evaluation metrics – Clustering

    Part 4 – KNN

    • Introduction to KNNs
    • KNNs as a classifier
    • Non Parametric algorithms and Lazy learning ideology

    And also,

    • Applications in Missing value imputes and Balancing datasets

    Part 5 – Advanced Regression Models

    • Introduction to regularization
    • Ridge regression

    Also, it covers –

    • Lasso regression

    Part 6 – Decision tree

    • Nonlinear models for classification
    • Intro to decision trees
    • Why are they called Greedy Algorithms

    In addition, It covers –

    • Information Theory – Measures of Impurity
    • Stopping criteria for trees
    • Susceptibility to overfitting and high variance

    And also,

    • Prevention of overfitting with Pruning or Truncation

    Part 7- Ensemble techniques

    • introduction to Bagging as an Ensemble technique
    • Bootstrap Aggregation and out of bag error

    Further, covering –

    • Random Forests and its Application in Feature selection
    • Scent and Boosting
    • How Boosting overcomes the Bias – Variance Tradeoff

    And also,

    • Gradient Boosting and Xgboost as regularized boosting

    Part 8 – Support Vector Machines

    • Introduction to Expectation–Maximization Algorithms
    • The kernel trick
    • Linear, Polynomial, and RBF kernels and their use cases

    Further, it has –

    • SVMs for regression and classification
    • Applications in Multiclass classification

    Part 9 – Bayesian Family Algorithms and Intro to Text

    Classification
    • Naive Bayes for Text classification
    • Bag of words and TF-IDF algorithm
    • Multinomial and Gaussian Naive Bayes

    And, also –

    • Bayesian Belief networks and Path models

    Part 10 – Time-series Analysis

    • Intro to Time series and its decomposition
    • Autocorrelation and ACF/PACF plots

    Further, it has –

    • The Random Walk model and Stationarity of Time Series
    • Tests for Stationarity – ADF and Dickey-Fuller test
    • AR, MA, ARIMA, SARIMA models for univariate time series
      forecasting

    And, also –

    • A regression approach to time series forecasting

    Part 11 – How to Build and Deploy a Machine Learning pipeline

    • Loading data
    • Feature engineering techniques
    • Principal Component Analysis for Dimensionality reduction

    In addition, covering –

    • Linear Discriminant Analysis
    • Feature Selection Techniques – Forward and Backward
    • elimination, RFE

    Further, it contains –

    • Model Tuning and Selection
    • Deploying a Machine Learning Model

    And, also –

    • Serving the model via Rest API

    Part 12 – AutoML

    • Introduction to AutoML
    • Auto learn

    Also, covering –

    • TPOT models
    • Auto Keras

    Module 4 – Deep Learning

    Part 1 – Neural Networks

    • introduction to Neural Networks
    • Layered Neural Network
    • Activation function and their application

    Also, it has –

    • Backpropagation and Gradient descent

    Part 2 – Tensorflow

    • Introduction to TensorFlow
    • Linear and Logistic regression with Tensorflow

    Part 3 – Artificial Neural Networks (ANNs)

    • Multi-layer perceptrons and Feedforward networks
    • Activation Functions
    • Intro to Deep Learning and deep neural networks

    Also, it contains –

    • Adam and Batch normalisation

    Part 4 – Deep Neural Networks

    • Designing a deep neural network
    • Optimal choice of Loss Function
    • Tools for deep learning models – Tflearn and Pytorch

    And, also –

    • The problem of Exploding and Vanishing gradients

    Part 5 – Convolutional Neural networks

    • Architecture and design of a Convolutional network
    • Pooling and Flattening layer

    Further, it contains –

    • Basics of digital images and image augmentation
    • Deep convolutional models

    Part 6 – Recurrent Neural networks and LSTMs

    • RNN network structure
    • Bidirectional RNNs and Applications on Sequential data
    • LSTM cell structure and its variants

    Additionally, it has –

    • Applying RNN/LSTMs to language and character modelling
    • Advanced Time series forecasting using RNNs with LSTMs

    And, also –

    • LSTMs vs GRUs – Key takeaways

    Part 7 – Restricted Boltzmann Machines and Autoencoders

    • Intro to RBMs and their training
    • Application of RBMs in Collaborative filtering
    • Intro to Autoencoders

    And, also –

    • Autoencoders for Anomaly detection

    Capstone Project

    • Self driving cars
    • Facial recognition

    Part 1 – Language modeling and Sequence tagging

    • Intro to the NLTK library
    • N-gram Language models: Perplexity and Smoothing
    • Introduction to Hidden Markov models

    Further, it contains –

    • Viterbi algorithms
    • MEMMs and CRFs for named entity recognition
    • Neural Language models

    And, also –

    • Application of LSTMs to predict the next word

    Part 2 – Vector space models of Semantics for Contextual

    Learning
    • Distributional semantics
    • Explicit and Implicit matrix factorization
    • Word2vec and Doc2vec models

    And also,

    • Introduction to topical modeling

    Part 3 – Sequence to Sequence tasks

    • Introduction to Machine translation
    • Word Alignment models and Encoder-Decoder Architecture

    And, also it has –

    • How to implement a conversational Chatbot

    Capstone Project

    • Fully functional Chatbot
      • What is RL ? – High-level overview
      • The multi-armed bandit problem and the explore-exploit dilemma
      • Markov Decision Processes (MDPs)

      Further, it has –

      • Dynamic Programming
      • Monte Carlo Control
      • Temporal Difference (TD) Learning (Q-Learning and SARSA)

      And, also it covers –

      • Approximation Methods (i.e. how to plug in a deep neural
      • network or other differentiable model into your RL algorithm)
      • Mathematics for Computer Vision
      • Intro to Transfer Learning
      • R-CNN and RetinaNet models for Object detection using Tensorflow

      Besides, the module covers –

      • FCN architecture for Image segmentation
      • IoU and Dice score for model evaluation

      And, also –

      • Face detection with OpenCV
      • Ethical Risk Analysis – Identification and Mitigation
      • Managing Privacy risks
      • Modeling personas with minimal private data sharing

      Also, it has –

      • Homomorphic encryption and Zero-Knowledge protocols
      • Managing Accountability risks with a Responsibility Assignment Matrix

      And, also –

      • Managing Transparency and Explainability risks

    Excel for Business

    Excel Fundamentals:
    • Introduction to Excel interface
    • Customizing Excel Quick Access Toolbar
    • Structure of Excel Workbook
    • Excel Menus

    Further, the module contains –

    • Excel Toolbars: Hiding, Displaying, and Moving Toolbars
    • Switching Between Sheets in a Workbook

    In addition, it covers –

    • Inserting and Deleting Worksheets
    • Renaming and Moving Worksheets

    Also, covering –

    • Protecting a Workbook
    • Hiding and Unhiding Columns, Rows and Sheets
    • Splitting and Freezing a Window
    • Inserting Page Breaks

    Besides, it contains –

    • Advanced Printing Options
      Opening, saving and closing Excel document
    • Common Excel Shortcut Keys
    • Quiz
    Worksheet Customization
    • Adjusting Page Margins and Orientation
    • Creating Headers, Footers, and Page Numbers

    Besides, the module has –

    • Adding Print Titles and Gridlines
    • Formatting Fonts & Values

    Further, the module contains-

    • Adjusting Row Height and Column Width
    • Changing Cell Alignment
    • Adding Borders
    • Applying Colors and Patterns

    In addition, it contains –

    • Using the Format Painter
    • Formatting Data as Currency Values
    • Formatting Percentages

    Also, covering –

    • Merging Cells, Rotating Text
    • Using Auto Fill
    • Moving and Copying Data in an Excel Worksheet

    And, also –

    • Inserting and Deleting Rows and Columns
    Images and Shapes into Excel Worksheet
    • Inserting Excel Shapes
    • Formatting Excel Shapes
    • Inserting Images

    And, also –

    • Working with Excel SmartArt
    Basic work on Excel
    • Entering Values in a Worksheet and Selecting a Cell Range
    • Working with Numeric Data in Excel
    • Entering Text to Create Spreadsheet Titles

    Besides, there are –

    • Entering Date Values and using AutoComplete
    • Moving and Copying Cells with Drag and Drop
    • Using the Paste Special Command

    Also, it has –

    • Inserting and Deleting Cells, Rows, and Columns
    • Using Undo, Redo, and Repeat
    • Checking Your Spelling

    Further, it has –

    • Finding and Replacing Information from worksheet & workbook
    • Inserting Cell Comments
    • Working with Cell References

    In addition, it contains –

    • Working with the Forms Menu
    • Sorting, Subtotaling & Filtering Data
    • Copy & Paste Filtered Records

    And, also –

    • Using Conditional Formatting
    • Use of Data Validation
    Excel Formulas
    • Creating Basic Formulas in Excel
    • Relative V/s Absolute Cell References in Formulas

    Besides, covering –

    • Understanding the Order of Operation
    • Entering and Editing Text and Formulas
    • Fixing Errors in Your Formulas

    And, also –

    • Formulas with Several Operators and Cell Ranges
    • Quiz
    Excel Functions
    • Introduction to excel functions
    • Learn about SUM() Function

    In addition, it covers –

    • Work with the MIN() and MAX() Functions
    • Get your hands on the AVERAGE() Function

    Further, it has –

    • Working with the COUNT() Function
    • Adjacent Cells Error in Excel Calculations
    • Use of AutoSum command
    • AutoSum shortcut key

    And, also –

    • Using the AutoFill Command to Copy Formulas
    • Quiz
    Working with Charts / Graphs
    • Creating a column Chart
    • Working with the Excel Chart Ribbon

    Also, the module has-

    • Adding and Modifying Data on an Excel Chart
    • Formatting an Excel Chart
    • Moving a Chart to another Worksheet
    • Resizing a Chart

    Besides, there are –

    • Changing a Chart’s Source Data
    • Adding Titles, Gridlines, and a Data Table
    • Formatting a Data Series and Chart Axis
    • Using Fill Effects

    And, also –

    • Changing a Chart Type and Working with Pie Charts
    • Quiz
    Data Analysis & Pivot Tables
    • Why Pivot Tables
    • Structuring Source Data for Analysis in Excel

    In addition, it contains –

    • Creating a PivotTable
    • Navigating & Manipulating the Pivot Table Field List
    • Exploring Pivot Table Analyze & Design Options

    Besides, there is –

    • Selecting, Clearing, Moving & Copying Pivot Tables
    • Refreshing & Updating Pivot Tables

    Further, it covers –

    • Dealing with Growing Source Data
    • Formatting Data with Pivot Tables
    • Enriching data with Pivot table calculated values & fields

    And, also –

    • Formatting and Charting a PivotTable
    • Pivot Table Case Study
    • Quiz
    Basic Macros
    • Automating Tasks with Macros
    • Recording a Macro
    • Playing a Macro and Assigning a Macro a Shortcut Key

    SQL & MongoDB for Business

    Introduction to SQL
    • What is a Database?
    • Why SQL?
    • All about SQL

    And also, it covers –

    • Difference between SQL & MongoDB
    • Different Structured Query languages
    • Why MySQL?
    • Installation of MySQL

    Besides, there are –

    • DDL
    • SQL Keywords
    • DCL
    • TCL
    • Database Vs Excel Sheets
    • relational and database schema

    Also, it has –

    • Foreign and Primary Keys
    • database manipulation, management, and administration
    2. NoSQL Databases :
    • Topics – What is HBase?
    • HBase Architecture

    In addition, it contains –

    • HBase Components,
    • Storage Model of HBase,

    And, also –

    • HBase vs RDBMS
    • Introduction to Mongo DB, CRUD
    • Advantages of MongoDB over RDBMS
    • Use cases
    First Step in SQL Database
    • Creating Database
    • Dropping Database

    Also, it has –

    • Using Database
    • Introduction to Tables
    • Data types in SQL

    Further, the module has –

    • Creating a table
    • Dropping table
    • Coding best practices in SQL
    SQL Fundamental Statements
    • SELECT Statement
    • COUNT
    • SELECT WHERE
    • ORDER BY

    Also, it covers –

    • IN, NOT IN
    • NULL and NOT_NULL
    • Comparison Operators (=, >, >=, <, <=)
    • MySQL Warnings (Understand and Debug)
    Refining Selection
    • SELECT DISTINCT
    • LIKE, NOT LIKE, ILIKE

    And also, it contains –

    • LIMIT
    • BETWEEN
    • BETWEEN – AND
    SQL Intermediate Statements
    • Multiple INSERT
    • INSERT INTO
    • GROUP BY
    • HAVING

    Further, it has –

    • WHERE vs HAVING
    • UPDATE
    • DELETE

    And, also –

    • AS
    • EXISTS-NOT EXISTS
    Aggregator Functions
    • Application of Group By
    • Count Function

    And, also –

    • MIN and MAX
    • Sum Function
    • Avg Function
    JOINS
    • Introduction to JOINs
    • INNER Join

    Further, it covers –

    • OUTER Join
    • Full Join

    Also, it contains –

    • Left Join
    • Right Join
    • UNION
    SQL String Functions
    • Loading Data
    • CONCAT
    • SUBSTRING
    • REPLACE
    • REVERSE

    Besides, there are –

    • CHAR LENGTH
    • UPPER & LOWER
    • TRIM, LTRIM, RTRIM

    And, also covering –

    • PATTERN MATCHING
    • REGULAR EXPRESSIONS
    Advance SQL
    • Local, Session, Global Variables
    • Timestamps and Extract
    • CURRENT DATE & TIME, EXTRACT, AGE
    • TO_CHAR

    Further, including –

    • Mathematical Functions and Operators
    • CEIL & FLOOR, POWER, RANDOM, ROUND, SETSEED
    • Operators and their precedence

    Further, it has –

    • String Functions and Operators
    • SubQuery
    • Self-Join
    • ALTER table

    Additionally, there are –

    • CASE
    • COALESCE
    • CAST
    • NULLIF

    And, also –

    • Check Constarints
    • Views
    • Import & Export
    Basics and CRUD Operation
    • Databases, Collection & Documents
    • Shell & MongoDB drivers
    • What is JSON Data

    And also,

    • Create, Read, Update, Delete
    • Working with Arrays
    • Understanding Schemas and Relations
    MongoDB
    • What is MongoDB?
    • Charateristics, Structure and Features
    • MongoDB Ecosystem

    Further, it covers –

    • Installation process
    • Connecting to MongoDB database

    Besides, there is –

    • What are Object Ids in MongoDb
    • Data Formats in MongoDB
    • MongoDB Aggregation Framework
    • Aggregating Documents

    And, also –

    • What are MongoDB Drivers?
    • Finding, Deleting, Updating, Inserting Elements

    TABLEAU for Business

    Introduction to TABLEAU
    • What is TABLEAU?
    • Why use TABLEAU?

    Further, it contains –

    • Installation of TABLEAU
    • Connecting to data source
    • Navigating Tableau

    Also, there is –

    • Creating Calculated Fields
    • Adding Colors
    • Adding Labels and Formatting
    • Exporting Your Worksheet
    • Creating dashboard pages

    Additionally, it covers –

    • Different charts on TABLEAU (Bar graphs, Line graphs, Scatter graphs, Crosstabs, Histogram, Heatmap, Treemaps, Bullet graphs, etc.)
    • Dashboard Tricks
    • Hands on exercises
    Data Types in Tableau
    • Aggregation and Granularity
    • Preattentive Processing
    • Length and Position

    Besides, it has –

    • Reference Lines
    • Parameters
    • Tooltips

    Further, there is – 

    • Data Over Time – Tableau
    • Implementation
    • Advance Table Calculations
    • Creating multiple joins in Tableau
    • Relationships vs Joins

    And, also –

    • Calculated Fields vs Table Calculations
    • Creating Advanced Table Calculations
    • Saving a Quick Table Calculation
    • Writing your own Table Calculations

    Also, covering –

    • Adding a Second Layer Moving Average
    • Trendlines for Power-Insights
    Mapping & Analytics
    • Getting Started With Visual Analytics
    • Geospatial Data
    • Mapping Workspace

    Besides, it covers –

    • Map Layers
    • Custom Territories
    • Common Mapping Issues
    • Creating a Map, Working with Hierarchies
    • Coordinate points

    Further, it has –

    • Plotting Latitude and Longitude
    • Custom Geocoding
    • Polygon Maps
    • WMS and Background Image

    In addition, it covers –

    • Creating a Scatter Plot, Applying Filters to Multiple Worksheets
    • Analytics Pane
    • Sorting and grouping

    Also, it contains –

    • Working with sets, set action
    • Filters: Ways to filter, Interactive Filters
    • Regression Models
    • Trend Lines
    • Forecasting and Clustering

    And, further covering –

    • Control Charts
    • Box Plots
    • Hands-on: deployment of Predictive model in visualization
    Calculations
    • Calculated Fields
    • Calculation Syntax
    • Creating Calculated Fields
    • Aggregation & Aggregation Types
    • Common Calculation Functions

    And also, it has –

    • Basic Aggregate Functions
    • String Functions
    • Logical Functions

    Further, it contains –

    • Date Functions
    • Table Calculations
    • Addressing & Partitioning

    Besides, it has –

    • Level of Detail (LOD) Expressions
    • Choosing an LOD Type
    • Creating Parameters
    Dashboard and Stories
    • Working in Views with Dashboards and Stories
    • Dashboard Layout
    • Dashboard Sizing
    • Tiled vs. Floating
    • Dashboard Objects

    Further, including –

    • Formatting
    • Working with Sheets
    • Fitting Sheets

    Also, covering –

    • Legends and Quick Filters
    • Floating Objects
    • Stories
    • Sharing Dashboards

    Power BI for Business

    Introduction to Power BI
    • Why Power BI?
    • Account Types
    • Installing Power BI

    And, it also has –

    • Understanding the Power BI Desktop Workflow
    • Exploring the Interface of the Data Model
    • Understanding the Query Editor Interface
    Query Editor
    • Connecting Power BI Desktop to Source Files
    • Keeping & Removing Rows
    • Removing Empty Rows

    Further, it contains –

    • Create calculate columns
    • Make first row as headers
    • Change Data type
    • Rearrange the columns
    • Remove duplicates

    Besides, it covers –

    • Unpivot columns and split columns
    • Working with Filters
    • Appending Queries

    Also, it contains –

    • Working with Columns
    • Replacing Values
    • Splitting Columns

    And, also –

    • Formatting Data & Handling Formatting Errors
    • Pivoting & Unpivoting Data
    • Query Duplicates vs References
    • Append Queries

    Moreover, it contains –

    • Merging Queries
    • DIM-Region Table
    • Understanding “Extract”
    • Basic Mathematical Operations
    Visualization
    • Introduction
    • Line Charts
    • Pie Chart
    • Bar Charts
    • Stacked bar Chart

    Also, it covers –

    • Clustered Column Chart
    • Combo Chart
    • Treemap Chart

    Further, covering –

    • funnel Chart
    • Scatter Chart
    • Gauge Card
    • Matrix

    In addition, it has –

    • Table
    • Slicers
    • KPIs

    And, also –

    • Maps
    • Text boxes – Shapes – Images
    Working with Power BI
    • Working with Time series
    • Understanding aggregation and granularity
    • Filters and Slicers in Power BI
    • Maps, Scatterplots and BI Reports

    Further, it includes –

    • Creating a Customer Segmentation
    • Analyzing the Customer
    • Segmentation Dashboard
    • Waterfall, Map Visualization

    Also, it has –

    • Pie and Tree Map
    • Include and Exclude
    • Categories with no Data
    Data Models: Data and Relationship
    • Understanding Relationships
    • Many-to-One & One-to-One

    Besides, it has –

    • Cross Filter Direction & Many-to-Many
    • M-Language vs DAX (Data Analysis Expressions)
    • Basics of DAX
    • DAX Data Types

    Also, it contains –

    • DAX Operators and Syntax
    • Importing Data for DAX Learning
    • Resources for DAX Learning
    • M vs DAX
    • Understanding IF & RELATED
    • Create a Column

    In addition, it has –

    • Rules to Create Measures
    • Calculated Columns vs Calculated Measures
    • Understanding CALCULATE & FILTER

    Further, including –

    • Understanding “Data Category”
    • SUM, AVERAGE, MIN, MAX, SUMX, COUNT, DIVIDE, COUNT, COUNTROOMS, CALCULATE, FILTER, ALL
    Time Intelligence
    • Create Date Table in M
    • Create Date Table in DAX

    Further, it covers –

    • Display Last Refresh Date
    • SAMEPERIODLASTYEAR

    And, also –

    • TOTALYTD
    • DATEADD
    • PREVIOUSMONTH
    Modelling
    • Creating your first report
    • Modelling Basics to Advance
    • Modelling and Relationship

    Further, it contains –

    • Ways of creating relationship
    • Normalization – De Normalization

    And, also –

    • OLTP vs OLAP
    • Star Schema vs Snowflake Schema

    Why is an artificial intelligence course relevant?

    Most importantly, an artificial intelligence course in Hyderabad is highly sought because of the extensive application of the domain.

    Automobile

    Artificial intelligence plays a crucial role in fostering proactive automobile maintenance. For example, in autonomous vehicles. Moreover, a predictive potential available from artificial intelligence techniques also allows for proactive automobile maintenance. Furthermore, smarter automobile manufacturing and advanced driver assistance features are other potentials.

    E-Commerce

    The domain of E-commerce has become more personalized with the help of artificial intelligence. For instance, a shopping experience is transformed when recommendations are generated by machine learning algorithms. Besides, E-commerce retailers provide support to customers by using virtual assistance tools and chatbots. Also, artificial intelligence in e-commerce helps in sales as well as customer retention.

    Transportation

    Artificial intelligence is revolutionizing travel and transportation. Also, the scope of artificial intelligence in transportation is extensive, from predicting traffic accidents to optimizing traffic. Besides, by monitoring traffic data, artificial intelligence can help regulate traffic flow and reduce congestion inroads.

    Healthcare

    By implementing artificial intelligence in healthcare, smarter disease diagnosis is possible. Additionally, natural language processing makes it easier to document clinical findings. Furthermore, institutions manage medical records, administer payments, and provide clinical decision support based on AI.

    Upskill yourself with this artificial intelligence course in Hyderabad

    Customize your courses, work in live projects and get certification with artificial intelligence training

    Job search support with artificial intelligence course in Hyderabad

    Skillslash’s collaborative and live interactive artificial intelligence training in Hyderabad

    Expert Recommendation

    Recommended By
    Industry Experts

    ENQUIRE FOR COURSE NOW

    Enquire for Program to know more on career transition into  data science and AI domain





      Full Stack AI and Ml Certification Program

      89,000 + 18% GST

      The Full stack Artificial Intelligence and Machine Learning course is specifically designed for working professionals. That said, the Full Stack Artificial Intelligence and Machine Learning course is specifically curated for those who wish to get hired as data science professionals in product-based companies and startups. In addition, earn valid certification.

      Clear

      Additional information

      Select Batch

      Weekend Batch: 27th November, Saturday, Weekday Batch: 8th November, Monday

      Frequently Asked Questions

      What are the prerequisites for enrolling in an artificial intelligence course in Hyderabad?

      Every enthusiastic data science aspirant, we feel, is qualified to make a successful data science career move. Also, no, we haven’t established any stringent eligibility requirements. However, we assess candidates’ eligibility on programming skills and statistical knowledge. However, the purpose of this eligibility check is to provide the right level of guidance. 

      Furthermore, we provide further support with module 0 to candidates with non-statistical and non-programming backgrounds. In addition, we teach them from the very beginning in module 0. Aside from that, an applicant must meet the following requirements.

      • Bachelor’s degree in any subject of technology or engineering. A master’s degree in computer science, technology, or business administration is also acceptable.
      •  At least one year of professional experience, either in IT or in a non-IT field.

      What is the length of the artificial intelligence course in Hyderabad and what are the topics covered in each module?

      The study period, which includes the three real-time industrial projects, might last anywhere from 8 to 10 months, depending on your schedule (weekdays/ weekends).

      In addition, the artificial intelligence training module is based on substantial market demand research in the industrial sector. These course modules also provide learning methodologies for the following topics, ranging from basic to advanced.

      • Python, C/C++, Java, and R programming
      • Applied mathematics
      • Data visualisation using Matplotlib and Pandas
      • Statistical concepts 

      Further, it covers: 

      • Hypothesis testing with ANOVA
      • Tensorflow based deep learning
      • ML modelling and algorithms

      And, also – Computer vision and Artificial Neural Networks. Moreover, there is extensive training with our artificial intelligence course in Hyderabad. Such as Tableau, MongoDB and Power BI.

      What types of learning methods are available in Skillslash's artificial intelligence course in Hyderabad?

      Most importantly, we provide both offline and online learning options. Aside from that, we have a hybrid learning mode designed specifically for working professionals. In particular, in hybrid learning mode, you can access all theoretical sessions via our live online sessions, but for practical projects, you will be working directly on the industrial project site.

      Are the instructors working professionals or academic scholars in data science?

      We intend to make all of our pupils highly employable in today’s work market. As a result, we only hire instructors who are working professionals with at least six years of experience teaching the modules in question.

      What are the advantages of the placement aid program under Skillslash's artificial intelligence course in Hyderabad?

      High-scoring resume building aid as part of our artificial intelligence training and placement support programme. In addition, there will be mock interview sessions to help you prepare for the interview for your desired career role. Also, you will receive guaranteed interview invitations from product-based MNCs and startups via referrals.

      Is it possible to have a make-up class if I miss one due to an unforeseen circumstance?

      Despite the fact that we offer live online classes, everyone of our students has access to recorded versions at any time. Also, we give you lifetime access to these recorded sessions, so you can watch them whenever you need theoretical advice in your data science career. So, there’s no need to be concerned if you miss any of the live classes. That being said, we strongly advise you to attend all live classes.

      Besides, we provide special scholarships to Covid affected candidates/ candidates who lost their job/ moms wanting to get back to the workforce after a career break.

      Is the placement programme equivalent to campusing at a university or college?

      We do not yet provide any campusing perks comparable to those provided by institutions. We provide comprehensive placement assistance. That is, we will prepare you for a certain employment role by providing you with real-world industrial project experience as well as a mock interview. Besides, once you’ve mastered the data science job market, we’ll start introducing you to product-based MNCs and startups.

      Besides, we provide special scholarships to Covid affected candidates/ candidates who lost their job/ moms wanting to get back to the workforce after a career break.

      What is the ‘job guarantee or money back’ program associated with Skillslash’s artificial intelligence course in Hyderabad?

      This add-on functionality is offered on our working professionals’ Full-Stack AI and ML course. Besides, our goal is to give comprehensive job aid to all qualified and potential prospects.

      You must meet the minimum score criteria to use this feature. Further, if even after satisfying these requirements, you are unable to get your desired employment in a startup or MNC within nine months of completing the course, we will return your whole course money.

      What is the cost of Skillslash’s artificial intelligence course in Hyderabad? Are there any discounts?

      The artificial intelligence course in Hyderabad has a course fee under 1 lakh. We have a scholarship programme for data science and artificial intelligence. 

      What is the Data Science (Artificial Intelligence) Scholarship programme from Skillslash?

      Firstly, every candidate will be given the opportunity to take a 20-minute online aptitude exam. If a candidate passes the aptitude exam with a score of more than 65 percent, he or she will be eligible for a 30 percent discount on the course expenses. In addition, candidates who lost their jobs as a result of the COVID situation, as well as mothers who want to begin their careers, can receive up to a 100% scholarship based on their exam score.

      Do I have to pay the costs all at once when I register?

      Most importantly, we provide two different payment options for the fees. During the final registration, you will be required to make a one-time payment. Besides, you can also make the monthly payment in instalments for the duration of the course. Aside from them, you can use popular credit cards to get a quick EMI and an education loan.

      Are there any fee discounts available for the artificial intelligence course in Hyderabad?

      If you are found to be eligible for the scholarship programme, you can save up to 30% on your course expenses. Furthermore, we offer specific scholarships to Covid affected candidates, candidates who have lost their jobs, and mothers who want to return to work after a career break.

      In this artificial intelligence course in Hyderabad, how many projects are included?

      The artificial intelligence course includes 15+ live projects from which you can select a handful for case study learning based on your domain specifications. Aside from that, you’ll have the opportunity to work on three industry projects (capstone projects) with various MNCs and startups during the following modules.

      What kind of certification does the artificial intelligence course in Hyderabad provide?

      Here is the catch – You will not receive any so-called certification or academic degree if you take the artificial intelligence course. Instead, we offer a highly regarded project experience certificate. Furthermore, this is issued directly by the company with which you completed your industrial project.

      What is the purpose of the Industrial project experience program's 'domain specialization tracking' feature?

      Our industry specialists faculty will assist you in identifying the appropriate employment role based on your domain knowledge. Also, from this you will be able to select the appropriate industrial project that will leverage your prior work experience.

      What distinguishes Skillslash's artificial intelligence training?

      Skillslash is the place to go if you're seeking for the best artificial intelligence institute in Hyderabad with a course curriculum that prioritises industry experience. Especially, what sets Skillslash's artificial intelligence training distinct is the one-on-one student:mentor attention you'll get throughout the programme. In addition, these classes, in particular, are entirely live and interactive, and they are led by artificial intelligence experts.

      Furthermore, here at Skillslash, you will have the unique opportunity to create your own courses to match your specific learning needs. Also, you can do so with the help of a professional. Besides, the data science and AIML courses are reasonable, and if you are coming from a non-IT background, you will receive additional aid in learning the basic modules. Specifically, these are also some of the reasons why Skillslash's artificial intelligence certification online training in Hyderabad is so effective.

      ...

      Know more about the learning modules of Skillslash’s artificial intelligence course in Hyderabad

      From milestone 0 to milestone 4, the artificial intelligence course syllabus is separated into milestones. Furthermore, you will receive expert-level artificial intelligence training from the ground up. Also, using case studies, capstones, and guided projects, you may learn everything from the fundamentals of programming and math to machine learning in depth.Besides, you will be schooled in sophisticated data science concepts such as deep learning and advanced computer vision. Natural language processing and auto AI are also on the table.
      In addition, you will be educated in resume preparation, interview coaching, and a practise test with experts in milestone 4. The data science and artificial intelligence course, in particular, is linked to live-industry projects, preparing you to solve real-world ML and AI problems. This best artificial intelligence school in Hyderabad will also provide you with the opportunity to obtain an artificial intelligence certificate.


      What are the main tasks and duties of artificial intelligence jobs?

      To put it another way, artificial intelligence jobs for freshers are concerned with the future potential of data. Moreover, managing the AI development process, as well as its creation and administration, are critical jobs. Moreover, jobs in machine learning and AI, in particular, include adopting a leadership role in enterprises and being essential decision-makers. Furthermore, the relevance of artificial intelligence job responsibilities generates a lot of interest for an artificial intelligence course in Hyderabad.


      What are the prerequisites for enrolling in Hyderabad artificial intelligence training?

      Before enrolling in any artificial intelligence school in Hyderabad, you need to first brush up on the fundamentals. This also entails honing your programming, statistical, analytical, and mathematical abilities. Furthermore, becoming a skilled data scientist or artificial intelligence engineer necessitates a deep understanding of linear algebra and calculus. Besides, computer languages such as Python and R can make learning a lot easier. Aside from that, it's necessary to hone critical thinking and problem-solving abilities. When it comes to interpreting patterns and trends, soft skills such as effective communication are also essential to communicate your opinions about data.


      Skillslash’s artificial intelligence course fees in Hyderabad

      Because of its inexpensive curriculum packages, Skillslash stands out as the finest artificial intelligence institute in Hyderabad for data science and ai ml courses. Skillslash courses are very affordable when compared to the typical artificial intelligence course expenses in Hyderabad. Moreover, artificial intelligence training is available through two major, cost-effective programmes: Data science for professionals, which is part of the Full Stack AI and ML curriculum, and a 9-month artificial intelligence course. Also, it's under a lakh in price.
      Most importantly, the Data Science and AI Internship Program is tailored to recent graduates and college students. Also, this curriculum, in particular, costs roughly $50,000 and lasts six months, with an internship beginning on the first day. Especially, with these plans, you can also get a three-year flexible membership. This Data Science and Artificial Intelligence programme in Hyderabad, in particular, offers a no-cost 5-month EMI scheme of Rs.10,000.


      How do you stay on top of the data science job market, given the high demand?

      To begin, you should learn from the best in the field of data science. For example, there are institutes in Hyderabad that provide the best artificial intelligence course with placement. Second, become involved in projects to get the most out of your education. It is critical to gain relevant industry experience in addition to academic theory. Industry experience, particularly in real-time and live projects.
      Most importantly, you will have the opportunity to master core data science from specialists at Skillslash. Furthermore, you will be able to obtain direct project certification from the companies. Also, you'll have the opportunity to network with industry leaders and learn from specialists. As a result, your portfolio will stand out from the crowd.

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