AI Landscape & Current Trends

• Understand the evolution of AI from machine learning to generative and agentic AI, including key industry applications and system types
 
• Explore AI career paths and domains such as ML, deep learning, NLP, and agentic systems, and how to choose the right track
 
• Learn AI project strategy, portfolio building, and gain exposure to tools like Google AI Studio and Claude

Python Programming

• Build strong programming fundamentals including data types, control structures, functions, and working with strings, lists, and dictionaries.
• Master advanced concepts like OOP, file handling, modules, APIs, and working with JSON and regular expressions.

• Work with Python tools such as Jupyter Notebook and VS Code for hands-on coding and development.

SQL & Data Warehousing

• Learn database fundamentals including normalization, keys, transactions, and relational database concepts
 
• Write efficient SQL queries using joins, subqueries, aggregations, window functions, and query optimization techniques

• Understand data warehousing concepts and integrate SQL with Python using modern database systems

Pandas for Data Handling

• Work with DataFrames for data loading, cleaning, filtering, and transformation across real-world datasets
 
• Perform operations like merging datasets, GroupBy analysis, pivot tables, and date-time handling

• Apply data manipulation techniques through mini projects using Pandas

Data Visualization using Python

• Create visualizations using bar charts, line plots, histograms, scatter plots, and advanced charts like heatmaps and pairplots
 
• Understand data storytelling, time series visualization, and choosing the right chart for different data scenarios
 
• Build styled visual outputs using Matplotlib and Seaborn for analysis and presentation