This workshop is designed for university students who want a 𝐜𝐥𝐞𝐚𝐫, 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐢𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, without getting lost in heavy theory or mathematical complexity.
We’ll start from the basics—what AI, Machine Learning, and Data Science actually are—and then move step by step through the full ML workflow using real datasets. You’ll see how raw data is cleaned, scaled, and prepared, and why this stage matters more than most people think.
From there, we’ll explore 𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 through hands-on examples:
- Classification with KNN, Naive Bayes, Logistic Regression, and SVM
- Regression (predicting numerical values)
- How models are trained, validated, and tested
- How predictions are actually made
In the second half, we move into 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 :
- Building a simple neural network using TensorFlow
- Understanding neurons, activation functions, loss, and gradient descent
- Seeing where neural networks outperform classical models
We’ll also cover:
- Unsupervised learning with K-Means and PCA for clustering and visualization
By the end of the workshop, you’ll have a solid mental model of how ML works, how to choose the right approach for a problem, and how to continue learning on your own.
𝐖𝐡𝐨 𝐬𝐡𝐨𝐮𝐥𝐝 𝐚𝐭𝐭𝐞𝐧𝐝?
This workshop is beginner-friendly. No prior Machine Learning experience is required—basic programming familiarity is enough.
𝐏𝐚𝐫𝐭𝐢𝐜𝐢𝐩𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐭𝐚𝐢𝐥𝐬:
- Participation is 𝐭𝐞𝐚𝐦-𝐛𝐚𝐬𝐞𝐝 (𝐞𝐚𝐜𝐡 𝐭𝐞𝐚𝐦 𝐧𝐞𝐞𝐝𝐬 𝐭𝐨 𝐛𝐫𝐢𝐧𝐠 𝐨𝐧𝐞 𝐥𝐚𝐩𝐭𝐨𝐩 𝐚𝐭 𝐥𝐞𝐚𝐬𝐭 𝐟𝐨𝐫 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐰𝐨𝐫𝐤𝐬)
- A team can have 𝐮𝐩 𝐭𝐨 𝟑 𝐦𝐞𝐦𝐛𝐞𝐫𝐬
- 𝐈𝐄𝐄𝐄 𝐌𝐞𝐦𝐛𝐞𝐫𝐬: BDT 300 per team
- 𝐍𝐨𝐧-𝐈𝐄𝐄𝐄 𝐌𝐞𝐦𝐛𝐞𝐫𝐬: BDT 400 per team
𝐋𝐮𝐧𝐜𝐡 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐩𝐫𝐨𝐯𝐢𝐝𝐞𝐝 𝐟𝐨𝐫 𝐚𝐥𝐥 𝐩𝐚𝐫𝐭𝐢𝐜𝐢𝐩𝐚𝐧𝐭𝐬.
If you’ve been curious about ML but didn’t know where to start, this workshop is built for you.
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐢𝐧𝐤:
https://docs.google.com/forms/d/e/1FAIpQLSdAF-LkYM-9XoyplMdiwJUUR7V6XR9G-6Ub_uKPCtQyJimJiw/viewform?usp=sharing&ouid=106628346034410452745
Also check out other Workshops in Dhaka.
