Develop practical data analytics skills with Data Analysis with Pandas and Python, a focused training course designed to help learners work confidently with structured and real-world datasets. The course introduces powerful Python-based techniques for organizing, cleaning, transforming, and analyzing data efficiently.
Course Overview:
Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data. On this course you will gain a fundamental understanding of Python Programming Language. Become a proficient Python programmer by learning along with skilled mentors. Learn how to search and navigate the tech documentation and efficiently handle errors and exceptions.
Get comfortable developing Python programs on your own through a series of coding exercises Become familiar with industry standards and learn the best practices for writing code Master your programming skills by working on real life projects; great for a resume building Create two of your projects for your portfolio of code.
Course Objectives:
- Installing
- Sorting
- Filtering
- Grouping
- Aggregating
- De-duplicating
- Pivoting
- Munging
- Deleting
- Merging
- Visualizing
Pre-requisites:
- Basic / intermediate experience with Microsoft Excel or another spreadsheet software (common
- functions, vlookups, Pivot Tables etc)
- Basic experience with the Python programming language
- Strong knowledge of data types (strings, integers, floating points, booleans) etc
Target Audience:
This Data Analysis with Pandas and Python training course is ideal for:
- Data Analysts and Business Analysts – Professionals who want to strengthen their data processing, analysis, and reporting skills using Python and Pandas.
- Excel Users – Professionals who want to move beyond spreadsheets and learn a more powerful and flexible approach to handling large datasets and automating data analysis tasks.
- Aspiring Data Analysts – Individuals who want to develop practical Python and Pandas skills as a foundation for a career in data analytics.
- Business Professionals – Professionals who regularly work with data and want to improve efficiency through Python-based data manipulation and analysis.
- Python Beginners – Learners with basic Python knowledge who want to apply their programming skills to real-world data analysis.
- Students and Recent Graduates – Individuals seeking practical data analytics skills that can complement their academic background and improve their career readiness.
- Researchers and Data-Driven Professionals – Individuals who need efficient tools for cleaning, transforming, analyzing, and interpreting datasets.
- Excel Power Users – Experienced spreadsheet users who want to automate repetitive tasks and handle larger or more complex datasets using Python and Pandas.
Course Duration:
- 14 hours – 2 days
Course Content:
Introduction to Python Programming
- What is Python?
- Why Python for Analysts?
- Basic Python operations
- Variable Types in Python
- Control Structures in Python
- Pillars of programming: Python built-in Data types
- Concept of mutability and behavior of different Data structures.
- Control flow statements: If, Elif and Else
- Definite and Indefinite loops: For and While loops
- Writing user-defined functions in Python
- Read and write Text files with python
- Learn how to manipulate data with Python
- Functions and Procedures
- Python lists, tuples and dictionaries.
Python as Object Oriented programming language
- Python classes, objects
- Python attributes and methods
- Inheritance
Functional Programming
Introduction to Jupyter
- Data analysis using python (numpy, pandas, series)
- Data visualisation using python libraries (ex; matplotlib, seaborn)
- Closing and Remarks
