Python Data Science course Syllabus

This IBM Professional Certificate offers a beginner-friendly introduction to Python programming for data science, designed to build practical skills in four comprehensive modules. The course spans approximately 12 weeks with a total time commitment of 60–80 hours, featuring hands-on labs and real-world data projects. Learners will progress from Python fundamentals to data analysis and visualization, culminating in a final project that demonstrates their proficiency. Each module includes coding exercises and practical applications to reinforce learning and prepare students for entry-level data science roles.

Module 1: Python Programming Fundamentals

Estimated time: 20 hours

• Variables, data types, and operators
• Control structures: loops and conditionals
• Functions and code modularity
• Lists, dictionaries, and basic data structures
• Introduction to object-oriented programming

Module 2: Working with Data Using Python

Estimated time: 20 hours

• Introduction to NumPy for numerical computing
• Data manipulation with Pandas DataFrames
• Data cleaning and preprocessing techniques
• Exploratory data analysis (EDA) workflows

Module 3: Data Visualization and Analysis

Estimated time: 20 hours

• Data visualization with Matplotlib
• Creating advanced plots using Seaborn
• Interpreting trends and patterns in data
• Applying descriptive statistics for insights

Module 4: Final Assessment and Practical Labs

Estimated time: 10 hours

• Hands-on coding exercises with real datasets
• End-to-end data analysis workflow
• Project submission for certificate eligibility

Module 5: Career Preparation and Next Steps

Estimated time: 5 hours

• Overview of job roles in data science
• Pathways to advanced topics like machine learning
• Using the IBM credential in job applications

Module 6: Final Project

Estimated time: 15 hours

• Deliverable 1: Analyze a real-world dataset using Python
• Deliverable 2: Visualize findings with Matplotlib and Seaborn
• Deliverable 3: Submit a comprehensive data analysis report

Prerequisites

• Basic computer literacy
• Familiarity with high school-level math
• No prior programming experience required

What You'll Be Able to Do After

• Write Python scripts for data manipulation and analysis
• Clean and preprocess real-world datasets using Pandas
• Create insightful visualizations with Matplotlib and Seaborn
• Perform exploratory data analysis on structured data
• Earn an IBM Professional Certificate to support job applications