12 WEEKS
VIRTUAL &
PHYSICAL
PROJECTS/
ASSIGNMENTS
CERTIFICATION
What You’ll Learn
By the end of this course, you will:
- Master Python for data science and apply libraries like Pandas, NumPy, and Seaborn.
- Collect, clean, and analyze data to uncover trends and insights.
- Build machine learning models using algorithms such as linear regression and k-means clustering.
- Design interactive dashboards with Power BI for business intelligence.
- Present a capstone project addressing real-world challenges in sectors like agriculture, finance, or logistics.
₦230,000
Why Enroll?
In a data-driven world, the ability to analyze and interpret data is a crucial skill.
At Ibadan Digital Academy, our 12-week Data Science program is designed to turn you into a data-savvy professional ready to tackle real-world challenges. This comprehensive curriculum covers Python programming, data wrangling, machine learning, visualization, and business intelligence, equipping you with the tools to make impactful decisions.
Localized Relevance:
Work on datasets and projects related to Nigerian industries like finance, agriculture, and logistics.
Hands-On Learning:
Weekly projects provide practical experience with real-world applications.
Global Competitiveness:
Prepare for certifications like Microsoft Data Analyst Associate and learn industry-standard tools.
Emerging Trends:
Stay ahead with neural networks, feature engineering, and ethical AI practices.
Portfolio Development:
Complete a capstone project to showcase your skills and impress potential employers.
Data Science Course Outline
Week 1: Introduction to Data Science and Programming
- Discover what data science is and its importance in decision-making.
- Learn Python basics, including variables, data types, and loops.
Week 2: Data Collection, Cleaning, and Exploration
- Handle missing data, clean datasets, and explore data types.
- Perform basic exploratory analysis to understand data distributions.
Week 3: Python for Data Science – Intermediate
- Utilize dictionaries, functions, and error handling in Python.
- Work with key libraries like Pandas and NumPy for data manipulation.
Week 4: Exploratory Data Analysis (EDA)
- Uncover patterns with summary statistics and visualizations.
- Create insightful plots using Matplotlib and Seaborn.
Week 5: Data Wrangling and Advanced Visualization
- Reshape and transform data using Python.
- Learn advanced visualization techniques to present complex insights effectively.
Week 6: Statistics for Data Science
- Explore probability theory, hypothesis testing, and correlation.
- Perform regression analysis to evaluate relationships in data.
Week 7: Introduction to Machine Learning
- Understand the differences between supervised and unsupervised learning.
- Train models using algorithms like linear regression and k-means clustering.
Week 8: Advanced Machine Learning Techniques
- Enhance models with feature engineering and optimization techniques.
- Explore neural networks for deeper learning.
Week 9: SQL for Data Science
- Write SQL queries, joins, and aggregations for data preparation.
- Combine SQL with Python for robust data analysis workflows.
Week 10: Business Intelligence Tools
- Use Excel and Power BI to analyze and visualize data.
- Create dashboards, pivot tables, and conditionally formatted reports.
Week 11: Ethical Data Science and Emerging Trends
- Understand data privacy laws like the Nigerian Cybercrimes Act.
- Analyze ethical dilemmas and case studies on data misuse.
Week 12: Capstone Project Presentation and Career Preparation
- Finalize and present a real-world data science project.
- Prepare for job applications with resume-building and interview coaching.
Tools Covered
