Python for Finance

This comprehensive Python course is designed to build a strong foundation in Python programming, with a special focus on data handling and analysis. Starting from the basics, learners will explore key concepts such as variables, datatypes, operators, and control structures (if-else, loops, functions, and lambda functions).

As the course progresses, students will gain proficiency in essential data structures including lists, tuples, dictionaries, and sets. The curriculum also covers modules, file handling, date management, and introduces learners to arrays using NumPy.

A major highlight of this course is its emphasis on data analysis, with hands-on practice using powerful Python libraries like Pandas, Matplotlib, and Seaborn. Basic statistical concepts such as mean, median, mode, standard deviation, and variance are also introduced to help students interpret data more effectively.

Finally, learners will discover how to leverage Google Colab for coding and use ChatGPT as a smart assistant to enhance their Python programming experience.

Whether you're a beginner or looking to strengthen your data handling skills in Python, this course provides the perfect blend of programming and practical data tools.

Who is this Course For?

This course is ideal for:

• Beginners who are new to programming and want to build a strong foundation in Python.
• College students from any stream looking to upskill in coding, data analysis, or preparing for tech-related careers.
• Finance, marketing, and operations professionals seeking to automate tasks, analyse data, or make data-driven decisions.
• Aspiring data analysts or data scientists who want to start their journey with Python-based tools.
• Non-tech professionals who want to future-proof their career by learning a versatile, in-demand skill.

Anyone curious about coding and looking to explore Python in a hands-on, practical way even without a prior background in technology.

Curriculum

1. Python Overview
2. Understanding Colab and Python Variables
3. Datatypes in Python
4. Understanding Print
5. Operators in Python
6. Datastructures in Python - List
7. Datastructures in Python - Tuples
8. Datastructures in Python - Dictionary
9. Datastructures in Python - Sets
10. If-Else (Decision Control)
11. Loops - While Loop
12. Loops - For Loop
13. Functions in Python
14. Lambda Functions
15. Array Introduction
16. Modules in Python
17. Managing Dates in Python
18. File Handling
19. Numpy
20. Pandas
21. Pandas for Data Analysis
22. Matplotlib
23. Seaborn
24. Basic Stats - Measures of Central Tendency
25. Standard Deviation and Variance
26. ChatGPT for Python Coding

About the Instructor

Head of Marketing, Digital Campaign and Operations Analytics with experience in Managing Analytics team along with building Predictive and Machine Learning models, Solving business problems using power of analytics in industries like Banking, Retail and Market Research