Course description
Dive into the essential building blocks of data science with our comprehensive foundation session. You'll learn to identify, collect, and validate data from various sources including databases, APIs, CSV files, and web scraping. Master data cleaning techniques to handle missing values, outliers, and inconsistencies that plague real-world datasets.
Build your first automated data pipeline using Python and industry-standard libraries like Pandas and NumPy. Understand data types, structures, and formats while implementing quality checks and validation rules. Learn to design scalable data workflows that can handle growing volumes of information.
Through hands-on exercises, you'll work with actual business datasets to create clean, reliable data foundations that serve as the backbone for all subsequent analysis and machine learning projects. By session end, you'll have built a complete data pipeline from raw source to analysis-ready dataset, establishing the critical skills needed for professional data science work.
Perfect for beginners - no prior programming experience required. All tools and techniques taught through practical, step-by-step implementation.
What will i learn?
- Collect, clean, and prepare datasets from various sources for analysis using industry-standard techniques
- Perform statistical analysis and hypothesis testing to identify significant patterns and trends in data
- Create professional data visualizations and interactive dashboards using Python, R, and business intelligence tools
- Build and interpret basic predictive models for forecasting and trend analysis
- Write SQL queries to extract and manipulate data from relational databases
Requirements
- Basic computer literacy and comfort with using spreadsheet software (Excel or Google Sheets)
- High school level mathematics (statistics background helpful but not required)
- Computer with at least 8GB RAM and stable internet connection for software installation and online labs
- Commitment to 6-8 hours per week for hands-on practice and project work
- Willingness to learn programming basics in Python and R (no prior experience needed)
Frequently asked question
No prior programming experience required! This course starts with fundamentals and builds progressively. We provide step-by-step guidance for Python and R programming basics, making it perfect for beginners. Our hands-on approach ensures you learn by doing, with plenty of practice exercises and support.
All required software is free and open-source. We'll guide you through installing Python, R, Jupyter Notebooks, and other tools. For cloud-based work, we provide access to online platforms. You'll need a computer with at least 8GB RAM and stable internet connection.
Our SET (Sangrenes Edu-Tech) methodology emphasizes hands-on practical learning with real business datasets. Instead of just theory, you'll work on actual projects that simulate workplace scenarios. Plus, you get personalized mentoring and career guidance throughout the course.
You'll complete 4-5 real-world projects including: customer behavior analysis for an e-commerce company, sales forecasting for a retail business, marketing campaign effectiveness study, and a final capstone project using data from your industry of choice.
