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Delve into Python programming and master data cleaning and visualization using Pandas and Seaborn. Designed for Grades 9 to 12, this program explores real-world case studies across diverse fields and concludes with a capstone project aligned with the UN Sustainable Development Goals.
PROGRAM HIGHLIGHTS
- Learn Python, Pandas & Seaborn libraries.
- Master key statistical concepts for Data Science & AI.
- Explore real-world case studies in diverse fields like healthcare, sports, and entertainment.
- Learn to work with large public datasets and extract meaningful insights.
- Work on a capstone project aligned with the UNSDGs.
PROGRAM STRUCTURE
- Duration: 3 weeks, 14 sessions
- Session Length: 2 hrs
- Format: All sessions are conducted live online via Zoom, ongoing support available via Slack
- Each session integrates real-world case studies, foundational AI concepts, and hands-on coding to explore, build, and apply knowledge effectively.
REQUIREMENTS
- High school students (Grades 9–12) or equivalent.
- Students with basic programming knowledge (e.g., Python, Scratch, Java).
- Students with strong analytical skills and a keen interest in Data Science & AI.
SCHEDULE & FEES
- Cohort 1: June 16 – July 03 (5:00 PM – 7:00 PM PST)
- Cohort 2: July 21 – Aug 07 (10:00 AM – 12:00 PM PST)
- Cohort 3: July 21 – Aug 07 (5:00 PM – 7:00 PM PST)
- Fee: $600
Curriculum Overview
Monday | Tuesday | Wednesday | Thursday | Friday | |
Week 1 | Introduction to DS & AI Overview of Data Science and AI, their impact on society, and career opportunities. | Introduction to Python Basics of Python programming, including syntax, data types, and simple operations. | Python Programming 1 Control structures, loops, and conditionals, lists, dictionaries. | Introduction to Statistics Key statistical concepts needed for data analysis, such as mean, median, and standard deviation. | Pandas 1 Introduction to Pandas for data manipulation, working with data frames, and exploring datasets. |
Week 2 | Pandas 2 Advanced data manipulation techniques, filtering, grouping, and aggregating data. | Visualization 1 Basics of visualizing data using charts and graphs, using Matplotlib and Seaborn. | Visualization 2 Creating impactful visualizations to convey insights effectively. | Data Ethics & Introduction to Capstone Understanding ethical considerations in data collection and usage; introduction to capstone project requirements. | Capstone Project Work Identifying datasets and defining a problem to solve related to a UN Sustainable Development Goal. |
Week 3 | Capstone Project Work Conducting data analysis, applying skills learned in the previous weeks. | Capstone Preparation Preparing project findings, creating visualizations, and summarizing insights. | Presentation Preparation Developing a presentation to communicate capstone findings effectively. | Culmination Final capstone project presentations, showcasing work to peers and mentors. |
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