Course Overview
- ›Installing Python on Windows/Mac
- ›Installing VS Code
- ›Installing Python Extension in VS Code
- ›Setting up Virtual Environment (venv)
- ›Installing Required Libraries (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn)
- ›Understanding Integrated Terminal
- ›Running Python Scripts in VS Code
- ›Managing Project Folder Structure
- ›What is Data Analytics?
- ›Types of Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
- ›Data Types, Data Sources and Formats
- ›Data Cleaning and Preprocessing Concepts
- ›Analytics vs Data Science vs AI
- ›Industry Use Cases
- ›Mean, Median & Mode
- ›Variance & Standard Deviation
- ›Probability Basics
- ›Normal Distribution
- ›Python Installation and Environment Setup
- ›Variables and Data Types
- ›Numeric Data Types (int, float)
- ›String Data Type and String Operations
- ›String Methods
- ›Type Casting in Python
- ›Conditional Statements
- ›For Loop
- ›While Loop
- ›Functions
- ›Lists, Tuples, Dictionaries, Sets
- ›Lambda Functions
- ›Basic OOP
- ›Introduction to Google Colab
- ›Creating Notebooks
- ›Code & Markdown Cells
- ›Installing Libraries
- ›Uploading Datasets
- ›Google Drive Integration
- ›Sharing Notebooks
- ›Arrays
- ›Indexing & Slicing
- ›Math Functions
- ›Multi-Dimensional Arrays
- ›CSV/Excel Handling
- ›DataFrames
- ›Data Cleaning
- ›Filtering & Sorting
- ›GroupBy
- ›Merging Data
- ›Line Charts
- ›Bar Charts
- ›Histograms
- ›Scatter Plots
- ›Box Plots
- ›Heatmaps
- ›Database Basics
- ›DDL, DML, DCL
- ›Tables & Constraints
- ›CRUD Operations
- ›Joins
- ›Subqueries
- ›Views
- ›ML Basics
- ›Types of ML
- ›Workflow
- ›Supervised vs Unsupervised
- ›Linear Regression
- ›Polynomial Regression
- ›Ridge & Lasso
- ›Decision Trees
- ›Random Forest
What we'll cover in this course:
- Setting up Coding Environment
- Introduction to Data Analytics (Interview Core)
- Statistics for Data Analytics
- Python Revision (for Data Science)
- Understanding Google Colab Notebook
- NumPy for Data Analysis
- Pandas for Data Preprocessing
- Data Visualization
- SQL Essentials
- Machine Learning Fundamentals
- Regression Algorithms
- Classification Algorithms
- Unsupervised Learning
- Artificial Intelligence
- Prompt Engineering
- LLM Integration
- Excel Basics
- Excel Formulas
- Advanced Excel
- Excel Charts
- Power BI
- AI Tools
- Freelancing Skills
- Freelancing Platforms
- Interview Preparation
- Portfolio Projects
Technologies & Tools
