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 | session_01.md | ||
| 2 | IT Foundations for Data Science | session_02.md | ||
| 3 | Design Thinking 1 | session_03.md | ||
| 4 | Design Thinking 2 | session_04.md | ||
| 5 | Software Development Life Cycle | session_05.md | ||
| 6 | Demystifying Terms: DS, ML, AI | session_06.md | ||
| 7 | Setting UP | session_07.md | ||
| 8 | Python : Data Types and Operators | session_08.md | Python_Datatypes_Operators.ipynb | Open in Colab, Open in Colab |
| 9 | Control Flow | session_09.md | ||
| 10 | Loops & Functions in Python | session_10.md | basics_of_functions.ipynb, iterative_statements_functions.ipynb | Open in Colab |
| 11 | Object Oriented Programming (OOP) | session_11.md | OOPs_basics.ipynb | Open in Colab |
| 12 | Coding Best Practices | session_12.md | ||
| 13 | Python Case Study | session_13.md | ||
| 14 | Version Control | session_14.md | ||
| 15 | Math Notations and Descriptive Statistics | session_15.md | ||
| 16 | Soft Skills: Communication Skills | session_16.md | ||
| 17 | Inferential Statistics | session_17.md | ||
| 18 | Statistics Case Study | session_18.md | ||
| 19 | Linear Algebra for Data Science | session_19.md | ||
| 20 | Probability for Data Science | session_20.md | ||
| 21 | Linear Algebra & Probability Case Study | session_21.md | ||
| 22 | Calculus for Data Science | session_22.md | ||
| 23 | Numpy and Pandas | session_23.md | numpy_pandas | |
| 24 | Case Study on Numpy and Pandas | session_24.md | ||
| 25 | Data Engineering with Python | session_25.md | ||
| 26 | SQL Basics and CRUD | session_26.md | ||
| 27 | Soft Skills: Emotional Intelligence | session_27.md | ||
| 28 | SQL Join, Groupby and Window Function | session_28.md | ||
| 29 | SQL Case Study | session_29.md | ||
| 30 | Read Data From Various Sources | session_30.md | Image_Processing.ipynb | |
| 31 | Data Aquisition Case Study | session_31.md | ||
| 32 | Data Ingenstion Techniques | session_32.md | ||
| 33 | ETL Vs. ELT | session_33.md | ||
| 34 | Data Warehousing Concepts | session_34.md | ||
| 35 | Data Visualization and Feature Engineering | session_35.md | Plotting.ipynb | Open in Colab |
| 36 | Tableau Dashboard Design | session_35.md | ||
| 37 | Tableau Case Study | session_37.md | ||
| 38 | Soft Skills: Teamwork and Collaboration | session_38.md | ||
| 39 | Handling Missing Values | session_39.md | ||
| 40 | Encoding, Scaling, Normalization, Corrleation | session_40.md | ||
| 41 | Case Study Data Preprocessing | session_41.md | Data_Preprocessing_2.ipynb | |
| 42 | Linear Regression | session_42.md | ||
| 43 | LR NB KNN Hyperparameters | session_43.md | Bias_Variance.ipynb | |
| 44 | SVM DT RF | session_44.md | ||
| 45 | Case Study on Supervised Learning | session_45.md | ||
| 46 | Bagging Boosting Stacking Cascading | session_46.md | Bagging_Boosting.ipynb | |
| 47 | K-Means Agglomerative Clustering | session_47.md | KMeans_Scratch.ipynb | |
| 48 | Case Study on Unsupervised Learning | session_48.md | ||
| 49 | Soft Skills: Problem Solving and Decision Making | session_49.md | ||
| 50 | Feature reduction vs Dimensionality reduction, DBScan,PCA | session_50.md | ||
| 51 | Introduction to HTML and CSS | session_51.md | ||
| 52 | Introduction to Flask | session_52.md | ||
| 53 | Fast API and Streamlit | session_53.md | ||
| 54 | Structing Data Science Projects | session_54.md | ||
| 55 | Cloud Fundamentals Devops and MLOps | session_55.md | ||
| 56 | Deep Learning | session_56.md | ||
| 57 | Prompt Engineering and GPT | session_57.md | ||
| 58 | Big Data Eco-System | session_58.md | ||
| 59 | Case Study | session_59.md | ||
| 60 | Soft Skills: Personal Branding and Professional Etiquette | session_60.md | ||
| 61 | Interview Skills | session_61.md | ||
| 62 | Mock Interview | session_62.md |