DS-Club
This is the initial build of the DS-Club website. I hope to add a lot more code before shipping this website
Project maintained by thomasthaddeus
DS Club
The DS Club 10-week program is a well-structured curriculum designed to guide members in learning about data science in an interactive and engaging way. Each week focuses on a different topic, which varies from basic concepts to hands-on workshops, networking, and project showcases.
Weekly Topics
Week 1: Overview of the DS Club
Week 2: Basics of Data Science{ .btn }
This week focuses on the foundational concepts of data science. We’ll cover topics such as the different roles in data science (data analyst, data engineer, data scientist), the data science process (data collection, cleaning, exploration, modeling, evaluation, and interpretation), and the tools commonly used in the field (Python, R, SQL).
Week 3: Hands-on Workshop: Python for Data Science
We will dive into the Python programming language, focusing on the skills needed for data analysis. Members will be introduced to Python syntax and data structures, as well as important libraries for data science such as Pandas and Numpy. We’ll practice reading data into Python, performing basic data cleaning, and conducting a simple data analysis.
Week 4: Guest Lecture
For this session, we’ll have a guest speaker from the industry or academia to share their experience and insights about data science. Topics might range from emerging trends, real-world applications, to career advice. A Q&A session will be included to allow club members to interact with the guest.
Week 5: Data Visualization Workshop
Data visualization plays a crucial role in data science. This week, we’ll learn about the basic principles of data visualization and get hands-on experience creating plots and charts using libraries/tools such as Matplotlib, Seaborn, ggplot, or Tableau.
Week 6: Machine Learning Basics
This session will introduce the concept of machine learning and its types, including supervised, unsupervised, and reinforcement learning. We’ll discuss basic algorithms, the concept of training and testing data, and the fundamentals of model evaluation. The session will also include a demonstration of a simple machine learning model using Python or another tool.
Week 7: Project Showcase
Members will have an opportunity to present their data science projects or analyses. This is a great way to share learning experiences, get feedback, and learn from peers.
Week 8: Mini Data Competition/Hackathon
We’ll host a mini data competition or hackathon where members will form teams and solve a real-world data problem. This will be a fun, engaging way to apply learned skills.
Week 9: Data Ethics Discussion
This week, we’ll engage in a meaningful discussion about the importance of ethics in data science, including real-world examples of ethical dilemmas. This will encourage members to think critically about the implications of their work.
Week 10: Wrap-up and Next Steps
In our final week, we’ll reflect on the past 10 weeks, discuss what was learned, what went well, and what could be improved. We’ll also collect feedback to improve future sessions and discuss plans for the club moving forward.
End Goal
The key to our club’s success is to make each week interactive and engaging, whether that’s through discussions, Q&A sessions, or collaborative activities.
Our aim is for all members to feel involved and gain the maximum benefit from their participation in the DS Club.
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