📘 DSA IRP February 2025

Reference repository containing a list of topics across various sessions from the Data Science and Analytics Industry Readiness Program 2025 course at ICT Academy of Kerala.

Session No.	Session Name	Notes	Notebook	Open in Colab
1	Life Skills #1	session_01.md
2	Life Skills #2	session_02.md
3	IT Foundation for Data Science 1	session_03.md
4	IT Foundation for Data Science 2	session_04.md
5	Demystifying Terms: DS, ML, AI	session_05.md
6	Setting UP	session_06.md
7	Control Flow	session_07.md	Python_Datatypes_Operators.ipynb, iterative_statements_functions.ipynb	Open in Colab, Open in Colab
8	Functions in Python	session_08.md	basics_of_functions.ipynb	Open in Colab
9	Object Oriented Programming (OOP)	session_09.md	OOPs_basics.ipynb	Open in Colab
10	Descriptive Statistics	session_10.md	Plotting.ipynb	Open in Colab
11	Inferential Statistics	session_11.md
12	Statistics Assignment	session_12.md
13	Linear Algebra	session_13.md
14	Probability	session_14.md
15	Linear Algebra & Probability Assignment	session_15.md
16	Numpy and Pandas	session_16.md	NumPy_Pandas_Sample.ipynb	Open in Colab
17	Numpy Pandas Assignment	session_17.md
18	Structured Query Language (SQL)	session_18.md	sqlite_lesson.ipynb	Open in Colab
19	SQL JOIN	session_19.md
20	SQL Assignment	session_20.md
21	Reading Data from Various Sources	session_21.md	Reading_and_Writing_Data.ipynb	Open in Colab
22	Data Acquisition Assignment	session_22.md
23	Feature Engineering and Visualization	session_23.md	Data_Preprocessing_2.ipynb	Open in Colab
24	Tableau Dashboard Design for Data Science	session_24.md
25	Tableau - Case Study	session_25.md
26	Intermediate Assessment 1 (EDA)	session_26.md
27	Types of Features	session_27.md
28	Data Scaling	session_28.md
29	Preprocessing - Case Study	session_29.md
30	Linear Regression & Regularization	session_30.md	Linear_Regression_Synthetic_Data.ipynb, Linear_Regression_Pipeline_Wine_Data.ipynb	Open in Colab, Open in Colab
31	Logistic Regression	session_31.md	Logistic_Regression_Simple_Data.ipynb, Logistic_Regression_KNN.ipynb	Open in Colab, Open in Colab
32	SVM, Decision Trees, Random Forest	session_32.md	svm_dt_rf.ipynb	Open in Colab
33	Case Study on Supervised Learning	session_33.md	Naive_Bayes_Pipeline.ipynb, Naive_Bayes_Pipeline_Non_Tech.ipynb	Open in Colab, Open in Colab
34	Bias-Variance Trade-Off	session_34.md	Bias_Variance.ipynb	Open in Colab
35	Clustering	session_35.md	K_Mean_Clustering_from_scratch.ipynb	Open in Colab
36	Case Study on Unsupervised Learning	session_36.md	unsupervised_Learning_K_means.ipynb	Open in Colab
37	Intermediate Assessment II	session_37.md
38	Feature Reduction	session_38.md	PCA_from_scratch.ipynb	Open in Colab
39	Introduction to HTML & CSS	session_39.md
40	Introduction to Flask	session_40.md
41	Streamlit and FastAPI	session_41.md
42	Designing Data Science or ML Systems	session_42.md
43	MLOps	session_43.md
44	Deep Learning	session_44.md	Image_Processing.ipynb	Open in Colab
45	Capstone Case Study	session_45.md	Bagging_Boosting.ipynb	Open in Colab
46	Soft Skills 3	session_46.md
47	Soft Skills 4	session_47.md
48	Resume Preparation	session_48.md
49	Mock Interview	session_49.md