Introduction to AI & DS Lab
B. Tech Minor Course, Class: ECE Semester: iV, Regulation: R23
B. Tech Minor Course, Class: ECE Semester: iV, Regulation: R23
B.Tech-AI&DS 23ADM2- Introduction To Artificial Intelligence and Data Science Lab L T P Cr. 0 0 3 3
Pre-requisite: Knowledge of Computer fundamentals & Data structures& Algorithms Course Educational
Objective: The objective of the course is to provide a strong foundation of fundamental concepts in Artificial Intelligence and a basic exposition to the goals and methods of Artificial Intelligence and also provide fundamentals of Data Science.
Course Outcomes: At the end of this course,
CO1 : Apply the basic principles of AI in problem solving using Python (Apply – L3)
CO2 : Implement different algorithms using Python(Apply – L3)
CO3 : Perform various operations using numpy and pandas(Understand - L2)
CO4 : Improve individual / teamwork skills, communication & report writing skills with ethical values.
List of Experiments (Artificial Intelligence)
1. Implementation of DFS for water jug problem using python
2. Implementation of BFS for tic-tac-toe problem using python
3. Implementation of Hill-climbing to solve 8- Puzzle Problem using python
4. Implementation of Monkey Banana
Problem using PROLOG List of Experiments (Data Science)
1. Creating a NumPy Array
a. Basic ndarray
b. Array of zeros
c. Array of ones d. Random numbers in ndarray
2. The Shape and Reshaping of NumPy Array
a. Dimensions of NumPy array
b. Shape of NumPy array
c. Size of NumPy array d. Reshaping a NumPy array
3. Indexing and Slicing of NumPy Array a. Slicing
1-D NumPy arrays b. Slicing
2-D NumPy arrays c. Slicing
3-D NumPy arrays d. Negative slicing of NumPy arrays
4. Perform following operations using pandas a. Creating dataframe b. concat() c. Adding a new column
5. 5. Read the following file formats using pandas d. Text files e. CSV files f. Excel files g. JSON files
6. Perform following visualizations using matplotlib h. Bar Graph i. Pie Chart j. Box Plot k. Histogram l. Line Chart and Subplots
Web References:
1. https://www.analyticsvidhya.com/blog/2020/04/the-ultimate-numpy-tutorial-for-data science- beginners/
2. https://www.analyticsvidhya.com/blog/2021/07/data-science-with-pandas-2-minutes-guide to-key- concepts/
3. https://www.analyticsvidhya.com/blog/2020/04/how-to-read-common-file-formats-python/
4. https://www.analyticsvidhya.com/blog/2016/07/practical-guide-data-preprocessing python-scikit- learn/ 5. https://www.analyticsvidhya.com/blog/2020/02/beginner-guide-matplotlib-data visualization- exploration python/
Experiments & Files