Machine Learning Foundations crash course, Online BBA, Semester 6:
This subject introduces the core ideas of machine learning, including supervised and unsupervised learning, model validation, ensemble methods like random…
- 9 video lessons
- 1h 52m
- Study notes
- 45 quiz questions
- Assignment
9 lessons in Machine Learning Foundations
Each lesson pairs one topic with a hand-picked video, trimmed to the part that teaches it.
About this subject
This subject introduces the core ideas of machine learning, including supervised and unsupervised learning, model validation, ensemble methods like random forest and boosting, text analytics, and responsible use of AI in business. After it, you will be able to explain how common ML models are built and evaluated, compare techniques such as bagging and boosting, and assess AI applications for bias, explainability and privacy risks.
- 1
Supervised vs Unsupervised Learning
Module 1, ML Basics: Supervised vs unsupervised learning
Lec-23: Supervised vs Unsupervised learning with real life example· Gate Smashers· 7 min
Study notes 5 quiz questionsWatch lesson - 2
Train-Test Split Explained
Module 1, ML Basics: Train-test split
Machine Learning Tutorial Python - 7: Training and Testing Data· codebasics· 7 min
Study notes 5 quiz questionsWatch lesson - 3
Overfitting and Cross-Validation
Module 1, ML Basics: Overfitting and cross-validation
Machine Learning Fundamentals: Cross Validation· StatQuest with Josh Starmer· 6 min
Study notes 5 quiz questionsWatch lesson - 4
Random Forest Explained
Module 2, Ensemble Methods: Random forest
StatQuest: Random Forests Part 1 - Building, Using and Evaluating· StatQuest with Josh Starmer· 9 min
Study notes 5 quiz questionsWatch lesson - 5
Boosting vs Bagging
Module 2, Ensemble Methods: Boosting
Lec-25: BAGGING vs. BOOSTING vs STACKING in Ensemble Learning | Machine Learning· Gate Smashers· 4 min
Study notes 5 quiz questionsWatch lesson - 6
NLP Basics and Sentiment Analysis
Module 3, Text Analytics & AI: NLP basics, Sentiment analysis
What is NLP (Natural Language Processing)?· IBM Technology· 10 min
Study notes 5 quiz questionsWatch lesson - 7
Generative AI in Business
Module 3, Text Analytics & AI: Generative AI in business
Integrating Generative AI Into Business Strategy: Dr. George Westerman· MIT Corporate Relations· 51 min
Study notes 5 quiz questionsWatch lesson - 8
AI Bias and Fairness
Module 4, Responsible AI: Bias and fairness
Algorithmic Bias and Fairness: Crash Course AI #18· CrashCourse· 11 min
Study notes 5 quiz questionsWatch lesson - 9
Explainable AI and Data Privacy
Module 4, Responsible AI: Explainability, Data privacy
Privacy and Data Protection in AI Systems· Safeshield Training· 7 min
Study notes 5 quiz questionsWatch lesson
Assignment
ML Strategy Memo for a Retail Bank: From Model Choice to Responsible Deployment
Less scrolling. More passing.
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Hand-picked video lessons
9 short lessons, each with the best YouTube explanation we could find, trimmed to the part that matters.
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Study notes
9 lessons come with a summary, key points, key terms and takeaways for quick revision.
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Quizzes
45 questions across the course, with the right answer and why, the moment you pick.
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Assignments
1 subject assignments with clear tasks, so you practise what each subject actually asks of you.
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Notebook
Write notes beside the video, stamped with the exact time, and jump back to that moment later.
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Progress that follows you
Completed lessons, quiz scores and where you stopped, saved to your account on every device.
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Live chat
A members-only live chat beside every lesson: doubts, tips, stickers and GIFs with your batch. One ₹19 pass opens every live chat.
The Online BBA live chat. Study together, live.
A live chat right beside the video, shared by everyone studying Online BBA. Ask a Machine Learning Foundations doubt mid-lesson, share a shortcut, celebrate a finished semester.
- Live chat beside every lesson
- One live chat for all of Online BBA
- Members-only stickers & GIFs
- One ₹19 pass opens every live chat
Online BBA live chat
Anyone else finding Machine Learning Foundations tricky? 😅
Lesson 2 cleared it up for me. Watch it before the quiz
Doing it now, thanks!
Starting Customer Relationship Management tonight if anyone wants to go together
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Machine Learning Foundations: common questions
This subject introduces the core ideas of machine learning, including supervised and unsupervised learning, model validation, ensemble methods like random forest and boosting, text analytics, and responsible use of AI in business. After it, you will be able to explain how common ML models are built and evaluated, compare techniques such as bagging and boosting, and assess AI applications for bias, explainability and privacy risks. It's the Machine Learning Foundations subject of Online BBA, Semester 6, in 9 lessons: Supervised vs Unsupervised Learning; Train-Test Split Explained; Overfitting and Cross-Validation; Random Forest Explained; Boosting vs Bagging; NLP Basics and Sentiment Analysis; Generative AI in Business; AI Bias and Fairness; Explainable AI and Data Privacy.
Yes. Every video lesson is free to watch without an account. A free login unlocks study notes, quizzes, the assignment, a notebook and progress that syncs across devices.
About 1h 52m of video across 9 lessons, plus time for notes and quizzes. Go at your own pace; your place is saved.
Yes: “ML Strategy Memo for a Retail Bank: From Model Choice to Responsible Deployment”. It comes after the last lesson, with a brief, clear tasks and how the work is judged.
A members-only live chat beside the video, shared by everyone studying Online BBA, where learners ask doubts, share tips and react with stickers and GIFs. One ₹19 pass, paid once from your InsideEdge wallet, opens the live chat for every degree.
No. It's a crash course to help you understand and revise the subject quickly. Use it alongside your official study material and assignments.