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Post Graduate Certification in Data Science & Machine Learning

2,800 Ratings

Our advanced Certificate program in Data Science and AI is designed to enhance your knowledge and understanding of data science and ML related concepts. Learn from MNIT faculty and industry specialists to master python, data wrangling, prediction algorithms, etc., through real-time projects and case studies.

In collaboration with

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Ranked #1 Data Science Program by India TV

Learning Format


Live Classes

12 Months

Career Services

by Intellipaat

Placement Assistance



Hiring Partners

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Advanced Certification in Data Science and AI

This advanced certification in Data Science and AI led by MNIT, Jaipur faculty is curated to make you proficient in leading IT tools and technologies through industry-grade projects.

PG Program Key Highlights

500 Hrs of Applied Learning
154 Hrs Self-paced Videos
100+ Live Session across 12 months
50+ Industry Projects & Case Studies
Adv. Certification by E&ICT Academy, MNIT
Live classes from MNIT Faculty & Industry Practitioners
Placement Assistance by Intellipaat
1:1 with Industry Mentors
24*7 Support
Designed for Working Professionals & Fresher's
1:1 mock interview
No Cost EMI Option

About E&ICT MNIT, Jaipur

Electronics & ICT Academy MNIT, Jaipur(E&ICT MNIT, Jaipur) is an initiative supported by MeitY, Govt of India. The courses provided by us emphasize bridging the gap between industry demand and academic approach to learning and providing a foundation to build your career in top IT companies.

In this Post Graduate certificate program in Data Science and Machine Learning, you will:

  • Receive certification from E&ICT, MNIT and Intellipaat
  • Receive live lectures from the MNIT faculty

Key Achievement of MNIT, Jaipur

  • Ranked 35 in NIRF 2020 Ranking among top engineering colleges
  • Ranked 23 by the Week in 2020 for engineering
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Program in Collaboration with Microsoft

Benefits for students from Microsoft:

  • Official study material from Microsoft
  • Industry-recognized certification from Microsoft
  • Real-time projects and exercises
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Who can apply for the Post Graduate Program in Data Science and AI?

  • Individuals with a bachelor’s degree and a keen interest in learning AI and data science
  • IT professionals looking for a career transition as data scientists and machine learning engineers
  • Professionals aiming to move ahead in their IT career
  • Machine learning and business intelligence professionals
  • Developers and project managers
  • Freshers who aspire to build their career in the field of machine learning and data science

What roles can a data science and AI professional 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


Data Science

Data Wrangling


Story Telling

Machine Learning

Prediction algorithms

Software Engineering




Data visualization

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Tools to Master

pyspark python jupyter Scipy numpy pandas hadoop matplotlib mapreduce SQL tableau Adv-Excel R
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Meet Your Mentors


Live Course Self Paced Industry Expert Academic Faculty


  • 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. 


  • 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. 

To master AI, it is significant to familiarize yourself with Git, GitHub, and their various concepts and methods. This module will help you with exactly that.

2.1 Introduction to Git
2.2 Architecture of Git
2.3 Working with remote repositories
2.4 Branching and merging
2.5 Git methodology
2.6 Git plugin with IDE (Eclipse)

Tools covered


In this module, you will get acquainted with the various libraries and functions in python to help you understand data science and machine learning concepts better.

3.1 PySpark
3.2 Python
3.3 NumPy
3.4 SciPy
3.5 Matplotlib
3.6 Pandas
3.7 Python script
3.8 Python variables

Tools covered

pyspark python jupyter Scipy numpy pandas

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, triggers, etc. 

SQL Optimization and Performance

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

Tools covered


As a data scientist, it is important to know how to design and build algorithms and analyze data. However, it is also important to explain that data in a story-like manner so that the members of the organization can understand the data and what information you have gathered from the same. This module will help you learn exactly that.

5.1 Practice data science concepts by building a story from data set
5.2 Develop questions that can be answered by the data set
5.3 Gain insights into the data using various plotting techniques and build a story

Machine learning is one of the core technologies involved in the field of artificial intelligence, apart from deep learning, neural networking, etc. This machine learning module will help you gain in-depth knowledge of the various theorems and techniques that play a significant role in the field of ML.

6.1 Regression Modeling: Logical and Linear
6.2 Classification Modeling: K-nearest neighbor, Naïve Bayes Theorem, and Support Vector Machines (SVM)
6.3 Random forest and decision tree models
6.4 Use of PCA, k-means clustering, and isolated forests for anomaly detection
6.5 Time-series prediction model and recommendation system
6.6 Selection, evaluation, and interpretation of models

Tools covered

python jupyter

In this module, you will master all the significant modules, concepts, and technologies to help you gain expertise in the field of machine learning. Also, you will learn in detail about the various prediction algorithms that are part of this technology.

7.1 Linear regression techniques
7.2Logistic regression techniques
7.3 Supervised learning
7.4 Unsupervised learning
7.5 Ensemble techniques

Tools covered

python jupyter

You have gained knowledge of the basic modules in machine learning and its various techniques. In this module, you will master the advanced-level techniques in this domain to prepare you for real-world scenarios.

8.1 Text mining
8.2 Social networking analysis
8.3 Recommendation systems
8.4 Time-series analysis

Tools covered

python jupyter

Apart from designing algorithms and crunching data, data science and machine learning experts are also required to write code and build software. In this module, you will learn to write the software code which will help you master the development of software prototypes and make them production-ready.

9.1 Coding
9.2 Testing
9.3 Debugging
9.4 Working with production systems

In this data science with PySpark module, our experts will teach you the numerous techniques involved data science using PySpark.

10.1 What is PySpark?
10.2 Need of Spark with Python
10.3 Fundamentals of PySpark
10.4 Advantages of PySpark over MapReduce
10.5 Use of PySpark in Data Science and Machine Learning

Tools covered

python spark pyspark mapreduce

This module will make you proficient in working with TensorFlow and Keras, among the other tools and methods that are involved AI, deep learning, and neural networking.

11.1 Introduction to Deep Learning and Neural Networks
11.2 Multi-layered Neural Networks
11.3 Artificial Neural Networks and Various Methods
11.4 Deep Learning Libraries
11.5 Keras API
11.6 TFLearn API for TensorFlow
11.7 DNNS (deep neural networks)
11.8 CNNS (convolutional neural networks)
11.9 RNNS(recurrent neural networks)
11.10 GPU in Deep Learning
11.11 Autoencoders and restricted boltzmann machine (rbm)
11.12 Deep Learning applications
11.13 Chatbots

Tools covered

tensorflow Keras

Natural Language Processing (NLP) and deep learning are a significant part of machine learning and artificial intelligence. This module will cover the various concepts and applications of deep learning and NLP.

12.1 Applications of NLP
12.2 Deep learning fundamentals

This module on computer vision and image processing will help you learn the basic and advanced level concepts and techniques that are required in artificial intelligence.

13.1 Basics of computer vision and OpenCV
13.2 Use of neural networking for image processing
13.3 Classification and clustering of an image using GANs, multitask classifiers, and k-means
13.4 Detection of object
13.5 Image segmentation
13.6 Computer vision trends

14.1 Why and when do we need MLOps?
14.2 AI pipelines
14.3 Training, tuning, and serving on the AI platform
14.4 Kubeflow pipelines on the AI platform
14.5 CI/CD for Kubeflow pipelines

Tools covered

python jupyter FastAPI Swagger Paperspace Postman TensorFlow_Lite TensorFlow_JS-1 Streamlit PyTorch spark pyspark

As a data science and AI professional, a large part of your job involves dealing with large volumes of datasets. Here, you will learn to do so using various Python libraries, Spark, and other tools.

15.1 Data collection from RSSs, web scraping, and APIs
15.2 Data cleaning and transformation for ML systems
15.3 Automatic transformation tools
15.4 SQL and NoSQL databases to deal with large sets of data
15.5 Spark
15.6 Pandas
15.7 SQL and Spark SQL
15.8 ScrappingHub

Tools covered

spark SQL NoSql pandas SparkSQL ScrappingHub

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.


  • 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

Case Study:

This case study will cover the following concepts:

  • Creating a dashboard to depict actionable insights in sales data.

Tools covered


After completion of the Advanced Certification program in Data Science and Machine Learning, you will work on a real-time capstone project which will help you implement and validate the various concepts and skills that you have learned in the training.

Apart from python, you must also be familiar with R programming to build a successful career in data science. This data science with R module covers the various techniques and concepts in R which play a vital role in data science.

18.1 Introduction to R
18.2 R packages
18.3 Sorting DataFrame
18.4 Matrices and vectors
18.5 Reading data from external files
18.6 Generating plots
18.7 Analysis of Variance (ANOVA)
18.8 K-means clustering
18.9 Association rule mining
18.10 Regression in R
18.11 Analyzing relationship with regression
18.12 Advanced regression
18.13 Logistic Regression
18.14 Advanced Logistic Regression
18.15 Receiver Operating Characteristic (ROC)
18.16 Kolmogorov-Smirnov chart
18.17 Database connectivity with R
18.18 Integrating R with Hadoop

Tools covered

  • 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.
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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

100+ Live Session across 7 months
50+ Industry Projects & Case Studies
154 Hours of Self-paced Videos
24*7 Support

Project Work

Projects will be a part of your Certification in Data Science and AI to consolidate your learning. It will ensure that you have real-world experience in data science and AI.

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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 and that will help you stay on track with your up skilling objective.


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 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 learners’ 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.

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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, make new friends – the possibilities are endless and our community has something for everyone!


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

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


Application Review

An admission panel will shortlist candidates based on their application



Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

$ 1,799

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Upcoming Application Deadline 22nd June 2024

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

Program Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 22nd June 2024 08:00 PM IST Weekend (Sat-Sun)
Regular Classes 22nd June 2024 08:00 PM IST Weekend (Sat-Sun)

Data Science and AI FAQs

Why enroll in this Post Graduate Certificate Program in Data Science and Machine Learning?

This Post Graduate Program in Data Science and Machine Learning is led by top professionals from MNIT and experts in the field. Their main goal is to make you proficient in the various concepts, skills, and techniques involved in the respective field and keep you on track with the latest market demands and technological advancements.

After completion of this Post Graduate program, you will receive a completion certificate from the E&ICT Academy, MNIT Jaipur. Moreover, you will be awarded an industry-recognized Post Graduate Certificate in Data Science and Machine Learning from Microsoft.

Intellipaat provides career services that include Guarantee interviews for all the learners enrolled in this course. EICT MNIT Jaipur is not responsible for the career services.

The trainers of the PG certification in Data Science and ML program are top professors from MNIT and experts from top industries across the world. They are selected after going through a rigorous process where their skills, knowledge, and teaching ability are tested so that we can provide you with the best training experience.

This is a completely online PG program in Data Science and Machine Learning conducted by our experienced trainers from MNIT, Jaipur.

In case you fail to attend one or more live lectures, you will receive the recording of the session within the next 12 hours. Besides, if you require any other assistance, you will have access to our 24/7 online assistance platform.

Once you complete the program, execute the projects, and meet all the requirements, you will receive a joint Post Graduate certification from E&ICT and MNIT, Jaipur, along with certifications from Microsoft.

After completing the Post Graduate Program, you will be eligible to go through several mock interview sessions to prepare for your job interview, along with resume preparation. Moreover, you will get at least three interviews scheduled from our 200+ global hiring partners.

To get 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.

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