About this Course

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Intermediate Level
Approx. 11 hours to complete
English
Subtitles: English

Skills you will gain

Statistical AnalysisMachine LearningPython ProgrammingComputer ProgrammingLinear Algebra
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
English
Subtitles: English

Offered by

Alberta Machine Intelligence Institute logo

Alberta Machine Intelligence Institute

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

What Does Good Data look like?

2 hours to complete
11 videos (Total 65 min), 2 readings, 3 quizzes
11 videos
Business Understanding and Problem Discovery9m
No Free Lunch Theorem5m
Exploring the process of problem definition7m
Data Acquisition and Understanding8m
Metadata Matters5m
Dealing with Multimodal Data2m
Features and transformations of raw data6m
Identifying Data from Problem5m
Case Study: Problem from Data6m
Weekly Summary What does good data look like?4m
2 readings
Machine Learning Process Lifecycle Review10m
Match Data to the needs of the learning Algorithm10m
3 practice exercises
Business Understanding and Problem Discovery (BUPD) Review10m
Data Acquisition and Understanding Review10m
Module 1 Quiz30m
Week
2

Week 2

2 hours to complete

Preparing your Data for Machine Learning Success

2 hours to complete
11 videos (Total 61 min)
11 videos
Converting to Useful Forms7m
Data Quality5m
How Much Data Do I Need?4m
Everything has to be Numbers6m
Types of Data5m
Aligning Similar Data4m
Imputing Missing Values7m
Data Transformations7m
Weekly Summary: Preparing your Data for Machine Learning Success1m
Data Cleaning: Everybody's favourite task4m
4 practice exercises
Data Warehousing Review10m
Everything has to be Numbers Review10m
Types of Data Review10m
Module 2 Quiz30m
Week
3

Week 3

5 hours to complete

Feature Engineering for MORE Fun & Profit

5 hours to complete
8 videos (Total 45 min), 2 readings, 4 quizzes
8 videos
Useful/Useless Features6m
How Many Features?5m
What is Unsupervised Learning6m
Feature Selection7m
Feature Extraction2m
Transfer Learning7m
Weekly Summary: Feature Engineering for MORE Fun & Profit1m
2 readings
Possibilities for Text Features10m
Word Embeddings10m
3 practice exercises
Understanding Features6m
Building Good Features6m
Understanding Transfer Learning4m
Week
4

Week 4

2 hours to complete

Bad Data

2 hours to complete
9 videos (Total 48 min)
9 videos
Generalization and how machines actually learn6m
Bias in Data Sources3m
Bias and variance tradeoff6m
Outliers5m
Skewed Distributions7m
Badness Multipliers4m
Live Data Danger6m
Weekly Summary: Bad Data1m
4 practice exercises
Mistakes Computers Make10m
Data: Skewed Distributions10m
Live Data Dangers10m
Module 4 Quiz30m

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About the Machine Learning: Algorithms in the Real World Specialization

This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application. After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results, and deploy it in the real world. You will also be able to anticipate and mitigate common pitfalls in applied machine learning....
Machine Learning: Algorithms in the Real World

Frequently Asked Questions

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    • 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 enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. 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.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. 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. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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