Python for Data Analytics, Machine Learning, and Generative AI: A
Comprehensive Guide is a
10-week course designed to build strong foundations in programming, data
analysis, and AI. It equips learners—students, professionals, and beginners
alike, with practical skills to analyze data, build predictive models, and
create AI-driven content. Starting with Python, you’ll master key libraries
like NumPy, Pandas, Matplotlib, and Seaborn for data manipulation and
visualization. The course covers essential statistics for hypothesis testing.
You’ll explore supervised and unsupervised learning using scikit-learn, model
evaluation, and optimization. Advanced modules introduce Generative AI,
including GANs and Transformers, for creative applications in text and image generation.
A real-world capstone project ensures hands-on experience in solving business
problems. This course empowers learners to harness data and AI for innovation,
automation, and decision-making across industries.
| Course Status : | Upcoming |
| Course Type : | Core |
| Language for course content : | English |
| Duration : | 10 weeks |
| Category : |
|
| Credit Points : | 3 |
| Level : | Undergraduate/Postgraduate |
| Start Date : | 12 Jan 2026 |
| End Date : | 30 Apr 2026 |
| Enrollment Ends : | 28 Feb 2026 |
| Exam Date : | |
| Translation Languages : | English |
| NCrF Level : | 6.5 |
| Industry Details : | Accounting and Financial Services |
Week 1: Introduction to Python
for Data Science
Week 2: Data Structures &
Data Manipulation with Pandas and NumPy
Week 3: Data Cleaning &
Exploratory Data Analysis (EDA)
Week 4: Data Visualization with
Matplotlib & Seaborn
Week 5: Statistics for Data
Science (Mean, Median, Variance, Hypothesis Testing)
Week 6: Introduction to Machine
Learning (Supervised & Unsupervised Learning)
Week 7: Regression, Classification
Models with Model Evaluation & Optimization
Week 8: Introduction to
Generative AI (GANs, Transformers)
Week 9: AI Applications: Text
Generation, Image Synthesis, and Chatbots
Week 10: End-to-End Machine Learning Project (Data Pipeline, Model
Building, Deployment)
Dr. S. Ajitha, Associate Professor at M. S. Ramaiah University of
Applied Sciences, Bangalore, is an expert in Data Analytics, Machine Learning,
and Generative AI with over 17+ years of academic and industry experience.
Holding an M.Tech in Data Science and Engineering (BITS Pilani) and a Ph.D. in
Management, she bridges technology and business domains effectively. She has
conducted numerous Faculty Development Programs and workshops on Python, R, AI
and data-driven decision-making. Her research and publications focus on AI
integration, predictive modeling and generative AI applications in business and
finance, with several works published in Scopus-indexed and ABDC-listed
journals. She has also contributed book chapters with IGI Global and Routledge,
filed patents on AI-based predictive systems and led consultancy projects
involving AI-driven analytics and market research. Her teaching and research
emphasize applying Python for data analysis, machine learning model development
and generative AI solutions for real-world problem-solving.
Enrolling and learning from the course is free. However, if you wish to obtain a certificate, you must register and take the proctored exam in person at one of the designated exam centres. The registration URL will be announced when the registration form is open. To obtain the certification, you need to fill out the online registration form and pay the exam fee of Rs.750/-. More details will be provided when the exam registration form is published, including any potential changes. For further information on the exam locations and the conditions associated with filling out the form, please refer to the form.
Grading Components:
Internal Assignment Score: This contributes 25% to the final grade. It is calculated based on the average of the best 5 out of 10 assignments submitted during the course.
Proctored Final Exam Score: This contributes 75% to the final grade and is based on the proctored final exam, which is scored out of 100.
Overall Course Score: The overall course score is the weighted sum of the internal assignment score and the proctored final exam score.
Assessment Type | Weightage |
Weekend Assessment | 25% |
Final Exam | 75% |
Eligibility for Certification:
To qualify for the course certificate, you must meet both of the following criteria:
If either of these conditions is not met, you will not be eligible for certification, even if your final score is 40 or higher (out of 100).
Score | Type of Certificate |
>=90 | Gold |
76 - 89 | Silver |
61 - 75 | Bronze |
40 - 60 | Successfully Completed |
<39 | No Certificate |
Sample Certificate:
Disclaimer: In order to be eligible for the certificate, you must register for enrolment and exams using the same email ID. If different email IDs are used, you will not be considered eligible for the certificate.
The certificate of completion will include your name, photograph, and final exam score, along with a detailed score breakdown.
It will be electronically verifiable through the SWAYAM platform at https://swayam.gov.in/. Please note that only an e-certificate will be issued. Printed or hard copies will not be provided.
We sincerely appreciate your participation and interest in our online courses and certification programs. Wishing you continued success and an enriching learning experience with IIM Bangalore.
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