Microsoft baru saja nyediain kurikulum machine learning for beginners. Kurikulum ini bisa dipake buat belajar machine learning. Kurikulumnya dirancang buat 12 minggu, terdiri dari 26 pelajaran tentang mesin learning. Prakteknya pake library scikit-learn.

Setiap pelajaran ada kuis pretest dan post test, instruksi kuliah, solusi dan tugas. Kurikulum ini dirancang berbasis proyek. Link kurikulumnya bisa dilihat disini:

https://microsoft.github.io/ML-For-Beginners/#/

Mahasiswa kalo pengen ikutan belajar cukup fork repo githubnya kemudian mulai dari:

1. Kuis pre-lecture (kuliah)
2. Ikutin lecture dan menyelesaikan aktifitas yang ada disana
3. Membuat dan menyelesaikan projek; ada solusi juga yang disediakan disana
4. Ikut kuis post-lecture
5. Selesaikan challenge (tantangan)
6. Selesaikan assignment (tugas)
7. Tulis komen di discussion board di rubrik PAT (Progress assessment tool)

Materi prakteknya pake python, tapi ada juga beberapa materi yang tersedia dalam bahasa R. Ada banyak kuis, total ada 52, masing2 terdiri dari 3 pertanyaan. Daftar materinya bisa dilihat disini:

Lesson Number	Topic	Lesson Grouping	Learning Objectives	Linked Lesson	Author
01	Introduction to machine learning	Introduction	Learn the basic concepts behind machine learning	Lesson	Muhammad
02	The History of machine learning	Introduction	Learn the history underlying this field	Lesson	Jen and Amy
03	Fairness and machine learning	Introduction	What are the important philosophical issues around fairness that students should consider when building and applying ML models?	Lesson	Tomomi
04	Techniques for machine learning	Introduction	What techniques do ML researchers use to build ML models?	Lesson	Chris and Jen
05	Introduction to regression	Regression	Get started with Python and Scikit-learn for regression models	PythonR	JenEric Wanjau
06	North American pumpkin prices 🎃	Regression	Visualize and clean data in preparation for ML	PythonR	JenEric Wanjau
07	North American pumpkin prices 🎃	Regression	Build linear and polynomial regression models	PythonR	Jen and DmitryEric Wanjau
08	North American pumpkin prices 🎃	Regression	Build a logistic regression model	PythonR	JenEric Wanjau
09	A Web App 🔌	Web App	Build a web app to use your trained model	Python	Jen
10	Introduction to classification	Classification	Clean, prep, and visualize your data; introduction to classification	PythonR	Jen and CassieEric Wanjau
11	Delicious Asian and Indian cuisines 🍜	Classification	Introduction to classifiers	PythonR	Jen and CassieEric Wanjau
12	Delicious Asian and Indian cuisines 🍜	Classification	More classifiers	PythonR	Jen and CassieEric Wanjau
13	Delicious Asian and Indian cuisines 🍜	Classification	Build a recommender web app using your model	Python	Jen
14	Introduction to clustering	Clustering	Clean, prep, and visualize your data; Introduction to clustering	PythonR	JenEric Wanjau
15	Exploring Nigerian Musical Tastes 🎧	Clustering	Explore the K-Means clustering method	PythonR	JenEric Wanjau
16	Introduction to natural language processing ☕️	Natural language processing	Learn the basics about NLP by building a simple bot	Python	Stephen
17	Common NLP Tasks ☕️	Natural language processing	Deepen your NLP knowledge by understanding common tasks required when dealing with language structures	Python	Stephen
18	Translation and sentiment analysis ♥️	Natural language processing	Translation and sentiment analysis with Jane Austen	Python	Stephen
19	Romantic hotels of Europe ♥️	Natural language processing	Sentiment analysis with hotel reviews 1	Python	Stephen
20	Romantic hotels of Europe ♥️	Natural language processing	Sentiment analysis with hotel reviews 2	Python	Stephen
21	Introduction to time series forecasting	Time series	Introduction to time series forecasting	Python	Francesca
22	⚡️ World Power Usage ⚡️ – time series forecasting with ARIMA	Time series	Time series forecasting with ARIMA	Python	Francesca
23	⚡️ World Power Usage ⚡️ – time series forecasting with SVR	Time series	Time series forecasting with Support Vector Regressor	Python	Anirban
24	Introduction to reinforcement learning	Reinforcement learning	Introduction to reinforcement learning with Q-Learning	Python	Dmitry
25	Help Peter avoid the wolf! 🐺	Reinforcement learning	Reinforcement learning Gym	Python	Dmitry
Postscript	Real-World ML scenarios and applications	ML in the Wild	Interesting and revealing real-world applications of classical ML	Lesson	Team

Link githubnya:

https://github.com/microsoft/ML-For-Beginners

Semoga Bermanfaat!