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AI INSIGHTS
Explore Python programming, data analysis, and visualization in this 10-week course designed for high school students. Through dynamic online lectures and hands-on labs, students will practice and refine their skills each week and apply their learning in the capstone project where they analyze a social problem through the lens of data.
PROGRAM HIGHLIGHTS
- Explore real-world case studies in diverse domains like healthcare, sports, entertainment.
- Discover career pathways in Data Science and AI.
PREREQUISITES
- Basic programming knowledge in Python or a similar language.
- Strong analytical abilities and a keen interest in data and emerging technologies.
SKILLS AND IMPACT
- Develop foundational Python programming skills.
- Understand key statistical concepts essential for data science.
- Work with large public datasets to extract meaningful insights.
- Complete a capstone project aligned with a UN Sustainable Development Goal.
- Present your findings to a broader audience through a final presentation.
PROGRAM STRUCTURE
- The program includes 10 sessions introducing fundamental AI concepts and real-world applications.
- Each session features an AI case study, a skills-focused lesson, and a hands-on lab.
- Students complete assignments to reinforce learning, culminating in a capstone project that addresses a UN Sustainable Development Goal using public data insights.
- The capstone project lets students apply their skills to analyze complex challenges in their chosen domain.
PROGRAM SCHEDULE
Week 1 to 3 | Students will explore the core concepts of data science and its practical applications in the real world. They'll learn the basics of Python programming, covering topics like data types, conditional statements, branching, and essential data structures like Lists and Tuples. Through interactive lab sessions, students will have the opportunity to practice and apply their newfound knowledge. |
Week 4 to 6 | Students will dive into essential statistical concepts, including mean, median, mode, range, standard deviation, normal distribution, and correlation coefficients. They'll also gain proficiency in data manipulation using the Python Pandas library, learning how to handle CSV files, modify data, sort, query, and perform basic inferential statistics. In hands-on lab sessions, students will apply these skills using Colab Notebooks to practice data cleaning and manipulation. |
Week 7 to 8 | Students will explore data visualization with the Seaborn library, learning to create impactful graphs, charts, and plots. The focus will be on mastering best practices for clear and informative visual representations, empowering students to effectively interpret and communicate data patterns and trends. |
Week 9 to 10 | In the final two weeks, students will undertake a capstone project, applying all the skills they've acquired throughout the program. Their projects will focus on addressing a social issue aligned with the UN Sustainable Development Goals, utilizing public datasets for data manipulation and visualization. A key component of this experience is the culmination event, where students will showcase their analytical findings and insights, demonstrating their ability to tackle real-world challenges with data science. |
EARN A CERTIFICATE
Earn a completion certificate that will be validated by DIYA Research
