Python for Data Science
Data Science | Level: Beginner | Duration: 10 weeks
Current Price
₦200,000 ₦300,000
Students Enrolled
8,934
Rating
4.8 ⭐
Instructor
Okechukwu Kingsley
Data Science Lead. Has published over 20 research papers on machine learning and data analysis techniques. Experienced mentor and industry consultant.
Course Description
Start your data science journey with Python! This beginner-friendly 10-week course teaches you Python programming, data manipulation, visualization, and machine learning fundamentals. Gain hands-on experience analyzing real datasets, preparing data for analysis, and building predictive models using popular libraries.
Skills You'll Gain
- Python programming basics
- Pandas for data manipulation
- NumPy for numerical computing
- Matplotlib and Seaborn for visualization
- Data cleaning and preprocessing
- Statistical analysis and hypothesis testing
- Exploratory Data Analysis (EDA)
- Jupyter Notebooks for interactive coding
- Introduction to machine learning concepts
- Basic predictive modeling
Prerequisites
- Basic computer literacy
- High school level mathematics (algebra, statistics)
- No prior programming experience required
Curriculum
Python Fundamentals
- Installing Python and Jupyter Notebook Setup
- Variables, Data Types, and Basic Operators
- Control Flow: Conditionals and Loops
- Functions, Modules, and Packages
- File Input/Output and Exception Handling
- Introduction to Object-Oriented Programming
Data Manipulation with Pandas
- Introduction to Pandas DataFrames and Series
- Loading, Inspecting, and Exporting Data
- Data Cleaning: Handling Missing and Duplicate Data
- Data Transformation: Filtering, Sorting, and Grouping
- Merging, Joining, and Concatenating DataFrames
- Time Series Data Handling
Numerical Computing with NumPy
- Creating and Manipulating NumPy Arrays
- Mathematical and Statistical Functions
- Broadcasting and Vectorization Techniques
- Linear Algebra and Matrix Operations
- Random Number Generation and Simulations
- Performance Optimization Using NumPy
Data Visualization
- Basic Plotting with Matplotlib
- Creating Line, Bar, Scatter, and Histogram Charts
- Advanced Visualizations with Seaborn
- Customizing Plots and Themes
- Interactive Visualizations using Plotly
- Building Dashboards for Data Presentation
Real-World Data Projects
- Exploratory Data Analysis on Public Datasets
- Sales and Revenue Data Analysis Case Study
- Customer Segmentation with Clustering Techniques
- Introduction to Time Series Analysis
- Final Capstone Project: End-to-End Data Science Workflow
What You’ll Learn
- Write efficient Python code for data analysis
- Manipulate large datasets using Pandas and NumPy
- Visualize data insights with Matplotlib and Seaborn
- Perform statistical analysis to validate hypotheses
- Clean and preprocess raw data for analysis
- Explore real-world datasets to uncover patterns
- Build basic machine learning models
- Present findings via interactive dashboards
Course Features
- 50+ hours of structured video lectures and exercises
- 20 real-world datasets for hands-on practice
- Fully functional Jupyter notebook templates
- Weekly live Q&A sessions with instructor
- Assignments reviewed by industry mentors
- Job placement assistance and career advice
Additional Information
Certificate: Yes
Support: Instructor support available during business hours
Access: Lifetime access to course content and updates
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