About this Course

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Beginner Level

Basic coding (for loops, functions, if/else statements) & high school-level math (arithmetic, algebra)

Other math concepts will be explained

Approx. 33 hours to complete
English

What you will learn

  • Build machine learning models in Python using popular machine learning libraries NumPy & scikit-learn

  • Build & train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression

Skills you will gain

  • Regularization to Avoid Overfitting
  • Gradient Descent
  • Supervised Learning
  • Linear Regression
  • Logistic Regression for Classification
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level

Basic coding (for loops, functions, if/else statements) & high school-level math (arithmetic, algebra)

Other math concepts will be explained

Approx. 33 hours to complete
English

Offered by

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DeepLearning.AI

Placeholder

Stanford University

Syllabus - What you will learn from this course

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Week
1

Week 1

7 hours to complete

Week 1: Introduction to Machine Learning

7 hours to complete
20 videos (Total 147 min)
Week
2

Week 2

10 hours to complete

Week 2: Regression with multiple input variables

10 hours to complete
10 videos (Total 66 min)
Week
3

Week 3

16 hours to complete

Week 3: Classification

16 hours to complete
11 videos (Total 98 min), 1 reading, 5 quizzes

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About the Machine Learning Specialization

Machine Learning

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