UG Minor Program 2023
The course is specifically crafted for the advantage of second or third year undergraduate engineering students doing four year B Tech program in India. The course will commence in August 2023.
Introduction
This minor program is designed for individuals aiming to unlock a world of opportunities through a comprehensive machine learning learning approach. Participants can acquire in-demand skills from the comfort of their home, progressing at their own pace. This program paves the way to becoming a sought-after professional in the thriving field of artificial intelligence.
Immerse yourself in an interactive and live learning experience administered by IIIT Hyderabad’s expert faculty members. Whether you’re interested in hands-on projects, collaboration with experienced assistants, or building a robust foundation in modern machine learning, this program is tailored for you.
Who can participate?
- Students pursuing 4-year UG program in engineering/technology
- Students should be in their second or third year of UG engineering.
- Students should be studying in an AICTE recognised institution or a technical institution of repute in India.
- Students should be willing to spare at least three hours every week for learning the course.
What makes this program unique?
- B Tech Minor program in Modern Machine Learning
- Live online lectures and hands-on sessions with personalised learning experience
- Includes independent projects, quizzes and assignments.
- Equal focus on foundation and practices, with discussions with eminent professionals
What is the qualifying criteria?
- Strong interest to learn fundamentals of Machine Learning and Deep Learning
- Good academic performance at the end of second year in UG engineering
- Keen programming interest in Python in Colab environment
- Good appreciation of applications of Linear Algebra, Probability and Statistics
Regular Minor Program sessions start on 19 Aug 2023.
Curriculum
Grading Policy
- 25% weightage for assignments (GitHub)
- 75% weightage for examinations (online)
—————————————————— - Grades
Less than 40% – No certificate
40 – 59% – Completion Certificate
60 – 74% – B Grade
75 – 89% – A Grade
90% above – Outstanding
Module-Wise Examination Date and Time:
| Module Number | Module Name | Examination Date | Time |
|---|---|---|---|
| 1 | Representation and Learning | 29.09.2023 | 8.30 pm to 9.30 pm |
| 2 | Appreciating, Interpreting and Visualizing Data | 27.10.2023 | 8.30 pm to 9.30 pm |
| 3 | Classification 1: Nearest neighbour method | 24.11.2023 | 8.30 pm to 9.30 pm |
| 4 | Perceptron and Gradient Descent | 22.12.2023 | 8.30 pm to 9.30 pm |
| 5 | Classification 2: Powerful popular classifiers | 19.01.2024 | 8.30 pm to 9.30 pm |
| 6 | Regression and Regularization | 09.02.2024 | 8.30 pm to 9.30 pm |
| 7 | Unsupervised Learning | 07.03.2024 | 8.30 pm to 9.30 pm |
| 8 | Probabilistic Perspective | 05.04.2024 | 8.30 pm to 9.30 pm |
| 9 | MLP and CNN | 10.05.2024 | 8.30 pm to 9.30 pm |
Registered Students Details with Exam Score:
Grade Certificate
Certificates Issued for Participants after Completing Semester 1:
Certificates Issued for Participants after Completing Semester 2:
Certificates Issued for Participants after Completing Semester 3:
Feedback From Participants After First Semester:
Program Coordinator:
Teaching Assistant:
