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In this blog post, I will be talking about the course, Artificial and Computational Intelligence (ACI) in the M.Tech. in Data Science & Engineering program offered by BITS Pilani through the WILP mode.
This is a course named 'Artificial and Computational Intelligence' and is offered in the second semester of the M.Tech. program as an elective. There were two others electives offered - System for Data Analytics (SDA) and Data Visualization and Interpretation (DVI).
I do not know much about the other electives but will try and touch about them below:
SDA - This is a extension of COSS course in the first semester. It can be seen as COSS for data analytics. The course probably has some sections for the hardware aspects of data analytics as well.
DVI - As the name suggests it has to do with visualization of data with heavy usage of Tableau software.
Now, coming back to ACI, let me list the material that you need.
Artificial Intelligence: A Modern Approach by Pearson - Third Edition by Russel & Norvig: This is the best book for this course. The material is lucid and comprehensive. I feel that this book is more than enough.
The links to buy these books are given below:
On Amazon:
On Flipkart: https://www.flipkart.com/artificial-intelligence-modern-approach-3rd/p/itme9k74azgcezv3?pid=9789332543515
I bought this book from Amazon for Rs. 505. It was a used copy in good condition. A used book should be good.
I also bought two other books mentioned below. Both were used copies.
Artificial Intelligence: A New Synthesis by Nilsson - https://www.amazon.in/gp/product/8181471903/
ARTIFICIAL INTELLIGENCE Third Edition by Knight, Rich, and Nair - https://www.amazon.in/gp/product/0070087709/
According to me, these two books are not needed for the course but can be a good addition to your data science library at home.
The course handout can be found here: https://sacbitspilani.files.wordpress.com/2018/07/cs-f407-artificial-intelligence.pdf
This handout is for B.E. students but the M.Tech curriculum is quite similar.
The prerequisites for this course are - knowledge of a programming language (preferably Python) and a solid knowledge of Data Structures and Algorithms. The DSAD course in the first semester helps in laying the groundwork. Revise the concepts of algorithm design and graph theory - especially BFS and DFS and you are good to go!
This course primarily deals with how agents perceive the world and what actions do they need to take. Say for example, you need to build a self driving car - what does the car need to do in order to be a 'good' agent? The car should safely take its passengers from point A to point B. Thus, to be able to build such a system, we need to study the concepts of artificial intelligence by exploring search spaces, game playing, local search algorithms, constraint satisfaction problems,, first order logic, reasoning over time and reinforcement learning.
Overall, this course is really interesting so far and I hope I am able to apply what I study here in the near future.
I also referred to NPTEL videos given below:
I liked Sudeshna Sarkar's of IITKGP videos. I haven't seen the IITD videos.
Hope this helps!
Cheers,
Rupak
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