Python for Data Work
- Python basics and intermediate concepts
- Data structures, functions, and loops
- Working with files, strings, and libraries
Course Overview
Data Analysis
Build strong analytical foundations and create business-ready insights from raw data.
This program is designed for learners who want to become job-ready in data analysis with a practical focus on Python, Excel, visualization tools, and core statistics. You will learn how to clean, explore, analyze, and present data with confidence.
Duration
10-12 Weeks
Level
Beginner to Intermediate
Format
Live + Hands-on Practice
Outcome
Career-focused roadmap
What you will learn
Analyze datasets using Python, NumPy, and Pandas
Build visual stories with Matplotlib, Seaborn, Excel, Power BI, and Tableau
Apply statistics and probability to interpret data accurately
Present insights clearly to business and technical stakeholders
Who this course is for
Students starting a career in analytics
Working professionals moving into data roles
Anyone who wants to use data for decision-making
Program highlights
Python from basic to intermediate levelData analysis with NumPy and PandasVisualization with Matplotlib and SeabornExcel for reporting and analysisPower BI and Tableau exposureProbability and statistics essentials
Curriculum
Module-wise breakdown
The roadmap is organized from fundamentals to advanced implementation, so learners can build confidence step by step.
Data Analysis with Python
- NumPy
- Pandas
- Matplotlib
- Seaborn
Excel and BI Tools
- Basic Excel
- Power BI
- Tableau (optional)
Probability and Statistics
- What statistics is and why it matters
- Types of statistics
- Central tendency and dispersion
- Standard deviation
- Random variables
- Percentiles and quantiles
- Correlation and covariance
- Probability basics
- Probability distribution function and probability mass function
- Types of probability distribution
Ready to start your data analysis journey?
Get a structured learning path, hands-on practice, and career guidance tailored to this program.