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Advanced Certification in Data Science and AI

Learn Data Science and AI from IIT Faculty with Campus Immersion @ IIT Roorkee

Gain expertise in Machine Learning and Artificial Intelligence through an advanced certification program in Data Science and AI offered by iHUB DivyaSampark, a Technology Innovation Hub of IIT Roorkee, in collaboration with Intellipaat. Benefit from learning directly from IIT Faculty and industry experts, with personalized 1:1 mentorship, in this immersive online bootcamp.

Only Few Seats Left No Prior Coding Experience Required!

Ranked #1 Data Science Program by India TV

Learning Format

Online Bootcamp

Live Classes

7 Months

iHub - IIT Roorkee

Certification

Campus Immersion

IIT Roorkee

500+

Hiring Partners

About Program

This online Data Science and Artificial Intelligence advanced certification course conducted by the IIT Faculty aims at helping you master all the basic and advanced level skills that are crucial in the field of Data Science, Machine Learning, Deep Learning, and Artificial Intelligence.

Key Highlights

400 Hrs of Applied Learning
50+ Live sessions across 7 months
218 Hrs of Self-Paced Learning
Learn from IIT Faculty & Industry Practitioners
50+ Industry Projects & Case Studies
One-on-One with Industry Mentors
Placement Assistance
Resume Preparation and LinkedIn Profile Review
24*7 Support
Designed for Working Professionals & Freshers
1:1 Mock Interview
No Cost EMI Option
2 Days campus immersion at IIT Roorkee

Free Career Counselling

We are happy to help you 24/7

About iHUB DivyaSampark, IIT Roorkee

iHUB DivyaSampark aims to enable innovative ecosystem in new age technologies like AI, ML, Drones, Robots, data analytics (often called CPS technologies) and becoming the source for the next generation of digital technologies, products and services by promoting, enhancing core competencies, capacity building,Read More..

Key Achievements of IIT Roorkee:

Note: All certificate images are for illustrative purposes only and may be subject to change at the discretion of the iHUB - IIT Roorkee.

Career Transition

55% Average Salary Hike

$1,20,000 Highest Salary

12000+ Career Transitions

400+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Who Can Apply for the Course?

  • Individuals with a bachelor’s degree and a keen interest to learn AI and Data Science
  • IT professionals looking for a career transition as Data Scientists and Artificial Intelligence Engineers
  • Professionals aiming to move ahead in their IT career
  • Artificial Intelligence and Business Intelligence professionals
  • Developers and Project Managers
  • Freshers who aspire to build their career in the field of Artificial Intelligence and Data Science
Who can aaply

What roles can a person trained in Data Science & Artificial Intelligence play?

Senior Data Scientist

Understand the issues and create models based on the data gathered, and also manage a team of data scientists.

AI Expert

Build strategies on frameworks and technologies to develop AI solutions and help the organization prosper.

Machine Learning Expert

With the help of several machine learning tools and technologies, build statistical models with huge chunks of business data.

Applied Scientist

Design and build machine learning models to derive intelligence for the numerous services and products offered by the organization.

Big Data Specialist

Create and manage pluggable service-based frameworks that are customized in order to import, cleanse, transform, and validate data.

Senior Business Analyst

Extract data from the respective sources to perform business analysis, and generate reports, dashboards, and metrics to monitor the company’s performance.

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Skills to Master

Python

Data Science

Data Analysis

AI

GIT

MLOps

Data Wrangling

SQL

Story Telling

Machine Learning

Prediction algorithms

NLP

PySpark

Model

Data visualization

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Tools to Master

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Meet Your Mentors

Interested in This Program? Secure your spot now.

The application is free and takes only 5 minutes to complete.

Curriculum

Live Course Self Paced Industry Expert Academic Faculty

Python 

  • Introduction to Python and IDEs – The basics of the Python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling ,etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 

SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables 

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table. 
  • Stored procedures, rank function, SQL ROLLUP, etc.

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc. 
  • Clustered indexes, common table expressions.

Hands-on exercise: 

Writing comparison data between the past year and the present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

Extract Transform Load

  • Web Scraping, Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.

Data Manipulation Using Pandas

  • Loading the data, data frames, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross-validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib.
  • Regression plots, categorical plots, area plots, etc, with Python seaborn.

Descriptive Statistics – 

  • Measure of central tendency, the measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, Bayes’ theorem, central limit theorem. 

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.

Introduction to Machine Learning 

  • Supervised, Unsupervised Learning.
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.

Classification 

  • Introduction to classification problems, Identification of a classification problem, and dependent and independent variables.
  • How to train the model in a classification problem.
  • How to evaluate the model for a classification problem.
  • How to optimize the efficiency of the classification model.

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  • How to train the model in a clustering problem.
  • How to evaluate the model for a clustering problem.
  • How to optimize the efficiency of the clustering model.

Supervised Learning 

  • Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree – Creating decision tree models on classification problems in a tree like format with optimal solutions.
  • Random Forest – Creating random forest models for classification problems in a supervised learning approach.
  • Support Vector Machine – SVM or support vector machines for regression and classification problems.
  • Gradient Descent – Gradient descent algorithm that is an iterative optimization approach to finding the local minimum and maximum of a given function.
  • K-Nearest Neighbors – A simple algorithm that can be used for classification problems.
  • Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.

Unsupervised Learning 

  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  • Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data.

Performance Metrics

  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model.
  • r2, adjusted r2, mean squared error, etc.

Artificial Intelligence Basics 

  • Introduction to keras API and TensorFlow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning 

  • Introduction to Deep Learning (by Academic Faculty)
  • Deep neural networks
  • Convolutional Neural Networks 
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted boltzmann machine 

The Data Science capstone project focuses on establishing a strong hold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals: 

  • Extracting, loading and transforming data into usable format to gather insights. 
  • Data manipulation and handling to pre-process the data.
  • Feature engineering and scaling the data for various problem statements. 
  • Model selection and model building on various classification, regression problems using supervised/unsupervised machine learning algorithms.
  • Assessment and monitoring of the model created using the machine learning models.
  • Recommendation Engine – The case study will guide you through various processes and techniques in machine learning to build a recommendation engine that can be used for movie recommendations, restaurant recommendations, book recommendations, etc.
  • Rating Predictions – This text classification and sentiment analysis case study will guide you towards working with text data and building efficient machine learning models that can predict ratings, sentiments, etc.
  • Census – Using predictive modeling techniques on the census data, you will be able to create actionable insights for a given population and create machine learning models that will predict or classify various features like total population, user income, etc.
  • Housing – This real estate case study will guide you towards real world problems, where a culmination of multiple features will guide you towards creating a predictive model to predict housing prices.
  • Object Detection – A much more advanced yet simple case study that will guide you toward making a machine learning model that can detect objects in real-time.
  • Stock Market Analysis – Using historical stock market data, you will learn about how feature engineering and feature selection can provide you with some really helpful and actionable insights for specific stocks.
  • Banking Problem – A classification problem that predicts consumer behavior based on various features using machine learning models.
  • AI Chatbot – Using the NLTK python library, you will be able to apply machine learning algorithms and create an AI chatbot.

Elective

Power BI Basics

  • Introduction to PowerBI, Use cases and BI Tools , Data Warehousing, Power BI components, Power BI Desktop, workflows and reports , Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data ,M Query and Hierarchies in Power BI.

DAX 

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics  

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data.

Introduction to MLOps 

  • MLOps lifecycle
  • MLOps pipeline 
  • MLOps Components, Processes, etc

Deploying Machine Learning Models 

  • Introduction to Azure Machine Learning 
  • Deploying Machine Learning Models using Azure

Version Control 

  • What is version control, types, SVN.

GIT

  • Git Lifecycle, Common Git commands, Working with branches in Git
  • Github collaboration (pull request), Github Authentication (ssh and Http)
  • Merging branches, Resolving merge conflicts, Git workflow
  • Job Search Strategy
  • Resume Building
  • Linkedin Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.

Excel Fundamentals 

  • Reading the Data, Referencing in formulae , Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering 
  • Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security 
  • VBA Macros, Ranges and Worksheet in VBA 
  • IF conditions, loops, Debugging, etc.

Excel For Data Analytics 

  • Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.  

Data Visualization with Excel

  • Charts, Pie charts, Scatter and bubble charts
  • Bar charts, Column charts, Line charts, Maps
  • Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

Excel Power Tools 

  • Power Pivot, Power Query and Power View

Classification Problems using Excel

  • Binary Classification Problems, Confusion Matrix, AUC and ROC curve 
  • Multiple Classification Problems  

Information Measure in Excel

  • Probability, Entropy, Dependence 
  • Mutual Information 

Regression Problems Using Excel

  • Standardization, Normalization, Probability Distributions 
  • Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation
  • Linear Regression, Logistic Regression, Error in regression, Information Gain using Regression

Hands-on Exercise:

Classification problem using excel on sales data, and statistical tests on various samples from the population.

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Disclaimer
Intellipaat reserves the right to modify, amend or change the structure of module & the curriculum, after due consensus with the university/certification partner.

Program Highlights

50+ Live sessions across 7 months
218 Hrs of Self-Paced Learning
50+ Industry Projects & Case Studies
24*7 Support

Interested in This Program? Secure your spot now.

The application is free and takes only 5 minutes to complete.

Projects

Projects will be a part of your Advanced Certification in Data Science and AI to solidify your learning. They ensure you have real-world experience in Data Science and AI.

Practice 20+ Essential Tools

Designed by Industry Experts

Get Real-world Experience

Reviews

4.8 ( 1,034 )

Hear From Our Hiring Partners

Career Services By Intellipaat

Career Services

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions that will help you stay on track with your upskilling.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing Placement Readiness Test (PRT)

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Our Alumni Works At

Master Client Desktop

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, and make new friends – the possibilities are endless and our community has something for everyone!

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Intellipaat

Admission Details

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

Submit Application

Submit Application

Tell us a bit about yourself and why you want to join this program

Application Review

Application Review

An admission panel will shortlist candidates based on their application

Admission

Application Review

Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

$ 1,492

Upcoming Application Deadline 8th Oct 2023

Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.

Program Cohorts

Next Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 8th Oct 2023 08:00 PM IST Weekend (Sat-Sun)
Regular Classes 8th Oct 2023 08:00 PM IST Weekend (Sat-Sun)

Other Cohorts

Others Cohorts

Date Time Batch Type
Program Induction 8th Oct 2023 10:00 AM - 01:00 PM IST Weekend (Sat-Sun)

Frequently Asked Questions

How will I receive my certificate?

Upon completion of the Data Science and Artificial Intelligence training course and execution of the various projects in this program, you will receive a joint Advanced Certification in Data Science and Machine Learning from Intellipaat and iHUB DivyaSampark, IIT Roorkee.

Intellipaat provides career services that include placement assistance for all the learners enrolled in this course. iHUB DivyaSampark, IIT Roorkee is not responsible for career services.

The Advanced Certification in Data Science and AI course is conducted by leading experts from IIT Roorkee and Intellipaat who will make you proficient in these fields through online video lectures and projects. They will help you gain in-depth knowledge in Artificial Intelligence and Data Science, apart from providing hands-on experience in these domains through real-time projects.

After completing the course and successfully executing the assignments and projects, you will gain an Advanced Certification in Data Science and Machine Learning from Intellipaat and iHub, IIT Roorkee which will be recognized by top organizations around the world. Also, our job assistance team will prepare you for your job interview by conducting several mock interviews, preparing your resume, and more.

If you fail to attend any of the live lectures, you will get a copy of the recorded session in the next 12 hours. Moreover, if you have any other queries, you can get in touch with our course advisors or post them to our community.

There will be a two-day campus immersion module at IITR iHub during which learners will visit the campus. You will learn from the faculty as well as interact with your peers. The cost of travel and accommodation will be borne by the learners. However, the campus immersion module is optional.

To be eligible for getting into the placement pool, the learner has to complete the course along with the submission of all projects and assignments. After this, he/she has to clear the Placement Readiness Test (PRT) to get into the placement pool and get access to our job portal as well as the career mentoring sessions.

You will undergo below sessions:

  • Job Search Strategy Sessions
  • Resume Building
  • Linkedin Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.

Yes, you can upgrade to Executive Post Graduate Certificate in Data Science and AI from Advanced Certification in Data Science and AI. However, you have to reach out to support team within 2 months from your date of enrollment.

Please note that the course fees is non-refundable and we will be at every step with you for your upskilling and professional growth needs.

Due to any reason you want to defer the batch or restart the classes in a new batch then you need to send the batch defer request on [email protected] and only 1 time batch defer request is allowed without any additional cost.

Learner can request for batch deferral to any of the cohorts starting in the next 3-6 months from the start date of the initial batch in which the student was originally enrolled for. Batch deferral requests are accepted only once but you should not have completed more than 20% of the program. If you want to defer the batch 2nd time then you need to pay batch defer fees which is equal to 10% of the total course fees paid for the program + Taxes.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work

I’m Interested in This Program

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