Events

Week 3: Hands-on Workshop: Python for Data ScienceBasic Python programming skills with a focus on data analysis. Introduction to Python programming language Basic Python syntax and data structures (lists, tuples, dictionaries) Introduction to Python libraries for data science (Pandas, Numpy) Reading data into Python and performing basic data cleaning Simple data analysis using Python

Week 4: Data Visualization WorkshopHands-on workshop on data visualization using tools like Matplotlib or Tableau. Importance of data visualization in data science Basic principles of data visualization Introduction to visualization tools/libraries (such as Matplotlib, Seaborn, ggplot, or Tableau) Creating different types of plots and charts Hands-on exercise to create a visualization from a given dataset

Week5: Build-a-Chatbot Workshop

Week 6: Machine Learning BasicsIntroduction to Machine Learning, types of ML, and real-world examples. Definition of machine learning and its types (supervised, unsupervised, reinforcement) Basic algorithms in machine learning (linear regression, logistic regression, decision trees, k-means clustering, etc.) Understanding the concept of training and testing data Basics of model evaluation (accuracy, precision, recall, ROC curve, […]

Week 7: Project ShowcaseMembers present their own data science projects or analyses. Members can present their own data science projects. This could include outlining the problem, discussing the data set, the methodologies used, results, and conclusion. Other members can provide feedback, ask questions and learn from the work presented.

Week 8: Mini Data Competition/HackathonAn exciting mini-hackathon where members solve a data problem in teams. Introduction to the competition/hackathon theme and dataset Explanation of the rules and objectives Forming teams and beginning the competition Regular check-ins or help sessions as the competition progresses Presentations by each team and selection of a winner Remember that these […]

Week 9: Data Ethics DiscussionA session on the importance of ethics in data science, including real-world examples of ethical dilemmas. Discuss the importance of ethics in data science. Examples of ethical dilemmas and considerations in the field (privacy concerns, bias in data, transparency of algorithms, etc.). Group discussion or debate on a specific ethical topic […]

Week 10: Wrap-up and Next StepsReflect on the past 10 weeks, gather feedback, what was learned, what went well, what could be improved. Gather feedback from members on their experience and what they'd like to see in future sessions. Discuss plans for next sessions, possible guest speakers, events, or topics to cover. Thank and congratulate […]