AIML
The Artificial Intelligence and Machine Learning (AIML) branch arrived at the PESU RR campus in 2022 and expanded to the EC campus in 2023.
Semester-3
| Subject | Credits |
|---|---|
| SoC Design and Computer Architecture | 5 |
| Data Structures and its Applications | 5 |
| Web Technologies | 4 |
| Statistics for Data Science | 4 |
| Automata Formal Languages and Logic | 4 |
Semester-4
| Subject | Credits |
|---|---|
| Big Data | 5 |
| Computer Networks | 5 |
| Design and Analysis of Algorithms | 4 |
| Operating Systems | 4 |
| Mathematics for Machine Learning | 4 |
Semester-5
| Subject | Credits |
|---|---|
| Algorithms and Optimizations in Machine Learning | 5 |
| Database Management System | 5 |
| Software Engineering | 4 |
| Elective - I | 4 |
| Elective - II | 4 |
Semester-6
(Not released yet)
Points to Remember
The course of AIML is going to be heavier than CSE. Since the newer courses are tough, some of them may be relatively graded, but relying on that is never a good idea. Get ready for a grind.
Instead of DDCO, you will have SOC Design or SDCA for short. It is practically DDCO+MPCA, which are two courses you take in the third and fourth sem as a CSE major.
In the fourth semester, instead of MPCA, which is already covered as a part of SDCA, you have Big Data. You will also have Mathematics for Machine Learning, MML for short, which replaces Linear Algebra for you (this is a mix of linear algebra and vector calculus).
- SDCA, Big Data and MML are subjects you should be worrying about. They are not in the CSE syllabus, so there won’t be much material. Make sure to study DDCO and MPCA from CSE through slides for SOC Design, it’s a mix of the two.
- Web Technologies will need you to make a project. It’s a website of your own, so learn about React and other technologies as well as you can right now. It’ll help you later.
- MML requires you to learn not just linear Algebra but also calculus. Our papers were HIGHLY based on demonstration of understanding. There’s no question bank that’ll help you entirely, although if you’re ok with scoring 20/40 studying the QB is enough. Learn the concept thoroughly, it’ll help you in the coming semesters
- In the third sem AFLL, Stats are scoring subjects. In the fourth sem DAA and Networks are scoring subjects. Beware of DSA, it’s not hard, but it requires constant attention if you want a good grade.
- Big Data and OS (Operating Systems) will now require a chunk of your time too. Implement the code as often as you can and understand the concepts through Anand’s slides for OS. For Big Data, spark by examples and Stack Exchange are your best friends. Make sure you learn them thoroughly. (Line by line attention is usually required)