About this Course

6,351 recent views
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 11 hours to complete
Chinese (Traditional)
Subtitles: Chinese (Traditional)
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 11 hours to complete
Chinese (Traditional)
Subtitles: Chinese (Traditional)

Offered by

National Taiwan University logo

National Taiwan University

Syllabus - What you will learn from this course

Week
1

Week 1

1 hour to complete

Concept learning

1 hour to complete
6 videos (Total 73 min), 2 readings, 1 quiz
6 videos
1-2 Hypotheses ,Relation between Instance Space and Hypotheses14m
1-3 The Find-S Algorithm10m
1-4 Version Space and The List-Then Eliminate Algorithm12m
1-5 The Candidate Elimination Algorithm15m
1-6 Biased and Unbiased Hypothesis Space, Futility of Bias-Free Learning12m
2 readings
NTU MOOC 課程問題詢問與回報機制1m
課程投影片開放下載公告2m
1 practice exercise
Week 1 Quiz10m
Week
2

Week 2

2 hours to complete

Computational Learning Theory

2 hours to complete
8 videos (Total 120 min)
8 videos
2-2 Setting 3, PAC Learnable10m
2-3 Exhausting the Version Space: Definition, Theorem ,Proof and some examples19m
2-4 Shatter, Dichotomy, VC dimension14m
2-5 Some examples and discussion about VC dimension14m
2-6 Upper and Lower Bounds on Sample Complexity with VC dimension, The Mistake Bound for Algorithms14m
2-7 Optimal Mistake Bound13m
2-8 The Weighted-Majority Algorithm and its Bound11m
1 practice exercise
Week 2 Quiz16m
Week
3

Week 3

2 hours to complete

Classification

2 hours to complete
6 videos (Total 114 min)
6 videos
3-2 Learning Decision Tree, Information19m
3-3 Generalization and Overfitting, Kai Square Pruning,Rule Post-Pruning22m
3-4 Model Evaluation: Metrics for Performance Evaluation, Methods for Model Comparison19m
3-5 Ensemble: Embedding, Bagging and Boosting13m
3-6 Support Vector Machine: Optimization, Soft Margins, and Kernel Trick21m
1 practice exercise
Week 3 Quiz24m
Week
4

Week 4

3 hours to complete

Neural Network and Deep learning

3 hours to complete
9 videos (Total 151 min)
9 videos
4-2 Single-Layer Network and Perceptron Learning Rule15m
4-3 Multi-Layer Perceptron, Back Propagation Learning, Decline of ANN10m
4-4 Cascade Correlation Neural Networks, Deep or Shallow Structure23m
4-5 Deep Learning: Convolutional Neural Networks17m
4-6 LeNet 5, Dropout, ReLU and the Variants, Maxout, Residual Net18m
4-7 Recurrent Networks, Long Short-Term Memory (LSTM), Neural Turing Machine, Memory-Augmented Neural Networks (MANN)15m
4-8 Autoencoder: Denoising Autoencoder, Stacked Autoencoder and Variational Autoencoder12m
4-9 Generative Adversarial Net (GAN), AE+GAN and Its Applications16m
1 practice exercise
Week 4 Quiz16m

Reviews

TOP REVIEWS FROM 人工智慧:機器學習與理論基礎 (ARTIFICIAL INTELLIGENCE - LEARNING & THEORY)

View all reviews

Frequently Asked Questions

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

More questions? Visit the Learner Help Center.