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Integrated Program in

Data Science, Artificial Intelligence & Machine Learning

In collaboration with

Hero Vired’s Integrated program in Data Science, Machine Learning and Artificial Intelligence is designed to give you the right skills to analyze data and build complex models to solve business problems. Here's what you can expect:

Ranked #1 PG Data Science Course by Analytics India Magazine

80+ Live Sessions with faculty from industry and academia

Eligibility for an MITx MicroMasters® Program Certificate

Apply now

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Dates to be announced

Program Start Date

11 months

Duration

Bachelor’s degree

Eligibility

Dates to be announced

Application Deadline

Custom curated international curriculum

Live Learning Duration

308

Hours

Total Effort Required

704

Hours

Total Weekly Effort

Hours

Tools Covered

Syllabus

Program Brochure

For detailed curriculum and program structure, download the program brochure

Download Brochure

Python Programming

Installation and set-up, Python Basics - Variables, built-in functions (print, type, help, range, input,...)

Loops and simple operations, Data Structures and Operations (Lists and Tuple)

Data Structures and Operations (Dictionary, Set), Conditional Statements, Functions and methods

Python Modules overview - Pandas, Numpy - DataFrames & Arrays. Functions, Numpy Array Operations, OOPs and Debugging concepts, Overview of ML Libraries

Data analysis with Python

Pandas Basics - DataFrames & Arrays, reading files, row/column selection, sub-setting, EDA, variable creation, data summaries

Pandas Advanced - Visualization with matplotlib and Seaborn, Data profiling and analysis, variable correlation. Handling data anomalies, feature engineering

ML Mathematics

Mathematics Basics and Advanced

Linear Algebra: Vectors and Scalars, Matrices and Matrix operations, 2D/3D Plots, Functions, Limits and Derivatives, Notations, Numbers, Sequences, Points, Lines and Planes, Gaussian Distribution, Probability Density Functions

Predictive Modeling and ML

Industry Application, Core Concepts (Train & Test samples, model metrics)

Linear/ Non-linear Regression models and implementation in Scikit-learn

Classification models (Logistic, SVM) and implementation in Scikit-learn

Classification models (Decision Trees) and implementation in Scikit-learn

Ensemble Learning: Tree-based and others

Machine Learning with Python-From Linear Models to Deep Learning

Working with Linear Classifiers and Linearly Seperable Data

Estimatiing Model Parameters using Perceptron Algorithm and Gradient Descent

Working with Linear SVM

Linear Regression

Non Linear Models and Feature Maps

SVM with Kernels

Recommendation Engines using Memory Based and Model Based Methods (Matrix Factorization)

Introduction to Neural Networks: Activation Functions, Forward pass, Backward pass

Recurrent Neural Networks and Sequence Models

Convolutional Neural Networks, Using Pytorch for Neural Network Models Implementation

KMeans Clustering and EM Algorithm

Gaussian Mixture Models for Collaborative Filtering

Reinforcement Learning

Statistics Basics

Statistics Concepts - Descriptive Statistics (mean, median, variance, std. dev, percentiles)

Understanding Univariate and Multivariate Distributions through plots (Histograms, Bar Plots, Box Plots, Two-way Tables, Scatter Plots, Q-Q Plots)

Correlation, Inferential Statistics (Point & Interval Estimation and use of various statistics)

CLT and Law of large numbers

Foundations of Statistics

Parametric Statistical Models, Parametric Estimation and Confidence Interval

Delta Method and Confidence Intervals

Introduction to Hypothesis Testing, and Type 1 and Type 2 Errors

Total Variation Distance, Kullback-Leibler (KL) Divergence, and the Maximum Likelihood Principle, MLE

Covariance Matrices, Multivariate Statistics, and Fisher Information

Maximum Likelihood Estimation (Continued) and the Method of Moments, M Estimation

Hypothesis Testing: χ2 distribution and T-test, Hypothesis Testing: Wald’s test, Likelihood Ratio Test, and Implicit Hypothesis

Hypothesis Testing: χ2-test for Multinomial Distribution, Goodness of Fit Test; Hypothesis Testing: Kolmogorov-Smirnov Test, Kolmogorov Lilliefors Test, QQ-plot

Introduction to Bayesian Statistics; Jeffrey’s Prior and Bayesian Confidence

Linear Regression 1; Linear Regression 2

Introduction to Generalized Linear Model: Exponential Families; The Canonical Link Function

Deep Learning

Basic Text Processing and NLP: Using Regex, creating tfidf features, POS Tagging and dependency parsing

DL in Practice: Using tf/pytorch to build simple neural networks, understand automatic differentiation, carry out gradient computations

DL in NLP 1: LSTMs and GRUs, Encoder Decoder Architecture for Translation

DL in NLP 2: BERT based models

DL In Computer Vision1: Use transfer learning to build image classifiers. Build multiclass and multilabel classifiers

DL In Computer Vision2: Single Shot Object Detection, measuring Object Detector Performance, custom labelling and custom training

Get the Hero Vired Advantage

70-90% live interactive classes

100% Program Completion Rate

Personalised guidance & support

Others

Pre recorded Lectures

Low completion rate

No personalised assistance

Industry Leading Faculty

Learn from world-class faculty that will guide you through this certification program

Manoj Agarwal

Faculty, Hero Vired | 17+ years of experience

An expert in designing solutions using machine learning techniques. Specializes in multi-objective optimization techniques and evolutionary computations.

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Subhashis Majumder

Professor and HOD, Heritage Institute of Technology | 27+ years of experience

M.Tech in CS from IIT, he has been a full-time academic since 2003, with research spanning Social Networking, Data Analysis, and more.

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Maurya Malineni

Partner, Gamification Corner | 8+ years of experience

A skilled Data Scientist excelling in areas like statistics, machine learning, gamification, etc., he also adeptly applies numerous game techniques in practical scenarios.

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Siddarth Kothotya

Data Scientist, Algoritmo Lab | 4+ years of experience

A Data Analyst with hands on experience in Data Analytics, Data Science, Artificial Intelligence, and ML. Has previous experience as a Machine Learning Engineer.

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Programs with leading universities and organizations

In collaboration with

MIT Open Learning

Integrated With

National Skill Development Corporation

Get certified after you graduate from the program

Upon successful completion of this Data Science program, you will be eligible for the following certificate:

Hero Vired Certificate

Benefit from the Hero Group’s decades of research and understanding of the Indian education and job landscape.
* Certificates are indicative and subject to change

Achieve your career goals through our personalized career mentorship and guidance

CV and LinkedIn profile building

Interview preparation

1-1 Career coaching sessions

Testimonials

Hear what our Learners have to say about the Hero Vired experience

Hritwij Shrivastava

Integrated Program in Data Science, Machine Learning & AI

Application Process

A simple yet thorough application process that will help you learn key skills to supercharge your career

Step 1

Application Submission:

Complete and review the form before submission. A meticulously filled out application aids us in evaluating your educational objectives and facilitates your seamless enrollment into the program

Step 2

Offer Letter Receipt:

Upon successful application, you will receive an offer letter to enroll, encapsulating comprehensive details about the program, the associated fee structure, and the payment schedule.

Step 3

Block your seat:

Secure your seat by making a nominal payment to confirm your acceptance into the program.

*This is contingent upon specific program eligibility requirements, criteria, and any potential tests that may be incorporated as part of the enrollment procedure.

Upskill yourself with Hero Vired

70% to 90% Live Instructor-led Classes

Gamified & Interactive Learning

Discussion Forums and Community

Industry Simulation Projects & Case Studies

Practical Hands-on Learning Session

Career Assistance and Workshops

Data Science, Machine Learning & AI

Part-time

Starting at

₹12,116/month

Price:₹4,25,000 + GST

Start Application

Seeking Financial Aid?

Application Deadline:Coming Soon

Apply early to secure your seat

Frequently Asked Questions

Which key data science concepts are covered in this program?

1. Neural Networks

The program comprehensively covers Artificial Neural Networks (ANN) using Multi Layered Perceptrons for classification problems, Convolutional Neural Networks (CNN) for video analytics, Recurrent Neural Networks (RNN) for NLP and time series data, with relevant libraries (Keras, Tensorflow and PyTorch) and hands-on cases.

2. Probability and Statistics

The foundation of all ML and AI is in probability/statistics, optimization and linear algebra. Most so-called ‘data scientists’ do not understand these basics and thus try to implement libraries in a GIGO (Garbage-In-Garbage-Out) mindset.Our program covers these topics in detail but not as separate ‘theory’ material. These are treated as concepts and learning that we connect back closely to actual models and real-world applications.

3. Python and R

Python – the fastest growing software in the world is our primary tool for the program. You can also access most ML-AI libraries (Tensorflow, Keras and Pytorch) through Python.We also teach R because it is a software that is currently being used by many organizations. Additionally, R serves as a powerful tool for statistical analysis and visualization.

4. Tensorflow or PyTorch

We believe that as future creators you need to be tools agnostic. The program helps you master both Tensorflow and PyTorch because each comes with its own set of pros and cons. Tools will keep changing and evolving. But core concepts, programming skills, and business applications remain set in stone.

Who is this Data Science Program for?

If you wish to build a career in or pivot it towards Data Science, Machine Learning, and Artificial Intelligence and can invest 11 months to master it, this program is for you. Blending industry and academic material, it is the only comprehensive and integrated program of its kind. It is the perfect program for students and working professionals looking to add Data Science and related skills to their profiles.

What do you mean by Indian contextualization?

Nearly all Data Science and related programs showcase case studies, data sets, and analysis from a developed world context and viewpoint. While this is essential for learning, it does not allow you to understand the problems of data as they pertain to the Indian business context

Our program contains an entire module dedicated to understanding the technology, its applications, and its implications in the Indian context. We believe this is essential for anyone interested in working with data involving Indian companies and the Indian government or government agencies

Hero Vired is a leading LearnTech company dedicated to offering cutting-edge programs in collaboration with top-tier global institutions. As part of the esteemed Hero Group, we are committed to revolutionizing the skill development landscape in India. Our programs, delivered by industry experts, are designed to empower professionals and students with the skills they need to thrive in today’s competitive job market.

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