About this Course

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Start instantly and learn at your own schedule.
Flexible deadlines
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Beginner Level
Approx. 7 hours to complete
English

Skills you will gain

Data ScienceBusiness AnalyticsDecision-MakingData AnalysisBig Data
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.
Beginner Level
Approx. 7 hours to complete
English

Offered by

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EIT Digital

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Politecnico di Milano

Syllabus - What you will learn from this course

Week
1

Week 1

1 hour to complete

Introduction to Data-driven Business

1 hour to complete
3 videos (Total 13 min), 2 readings, 2 quizzes
3 videos
Data-driven Decision Making for Data-centric Organizations2m
What's Big Data? How Does It Relate to Data Science?6m
2 readings
Data-driven Decision Making for Data-centric Organizations15m
What's Big Data? How Does It Relate to Data Science?15m
2 practice exercises
Data-driven Decision Making for Data-centric Organizations3m
Big Data and Data Science10m
Week
2

Week 2

2 hours to complete

Terminology and Foundational Concepts

2 hours to complete
3 videos (Total 16 min), 3 readings, 3 quizzes
3 videos
Machine Learning9m
Solving Problems: Programming vs. Machine Learning3m
3 readings
Success Story: Data Science at Netflix30m
Machine Learning slides20m
Solving Problems: Programming vs. Machine Learning10m
3 practice exercises
Success Story: Data Science at Netflix5m
Machine Learning20m
Solving Problems: Programming vs. Machine Learning30m
Week
3

Week 3

3 hours to complete

Data Science Methods for Business

3 hours to complete
5 videos (Total 25 min), 5 readings, 5 quizzes
5 videos
Classification of User-generated Content to Recommend Restaurants2m
Product Recommendation Using Decision Trees and Random Forests2m
Hiring Employees Using Logistic Regression8m
K-means Clustering6m
5 readings
Linear Regression for Product Price Prediction10m
Classification User-generated Content to Recommend Restaurants10m
Product Recommendation Using Decision Trees and Random Forests10m
Hiring Employees Using Logistic Regression10m
Using k-means for Clustering10m
5 practice exercises
Linear Regression30m
Naive Bayes30m
Decision Trees and Random Forests30m
Logistic Regression30m
K-means Clustering6m
Week
4

Week 4

1 hour to complete

Challenges and Conclusions

1 hour to complete
2 videos (Total 12 min), 1 reading, 1 quiz
2 videos
Conclusions1m
1 reading
Data Science Challenges20m
1 practice exercise
Data Science Challenges30m

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