About this Course
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Intermediate Level

Data Analysis with Python

Approx. 14 hours to complete

Suggested: 5-6 weeks of study, 3-6 hours per week...

English

Subtitles: English

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Data Analysis with Python

Approx. 14 hours to complete

Suggested: 5-6 weeks of study, 3-6 hours per week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
1 hour to complete

Introduction to Machine Learning

In this week, you will learn about applications of Machine Learning in different fields such as health care, banking, telecommunication, and so on. You’ll get a general overview of Machine Learning topics such as supervised vs unsupervised learning, and the usage of each algorithm. Also, you understand the advantage of using Python libraries for implementing Machine Learning models.

...
4 videos (Total 24 min), 1 quiz
4 videos
Supervised vs Unsupervised5m
1 practice exercise
Intro to Machine Learning10m
Week
2
5 hours to complete

Regression

In this week, you will get a brief intro to regression. You learn about Linear, Non-linear, Simple and Multiple regression, and their applications. You apply all these methods on two different datasets, in the lab part. Also, you learn how to evaluate your regression model, and calculate its accuracy.

...
6 videos (Total 50 min), 5 quizzes
6 videos
Evaluation Metrics in Regression Models3m
Multiple Linear Regression13m
Non-Linear Regression7m
1 practice exercise
Regression10m
Week
3
5 hours to complete

Classification

In this week, you will learn about classification technique. You practice with different classification algorithms, such as KNN, Decision Trees, Logistic Regression and SVM. Also, you learn about pros and cons of each method, and different classification accuracy metrics.

...
9 videos (Total 81 min), 5 quizzes
9 videos
Introduction to Decision Trees4m
Building Decision Trees10m
Intro to Logistic Regression7m
Logistic regression vs Linear regression15m
Logistic Regression Training13m
Support Vector Machine8m
1 practice exercise
Classification10m
Week
4
4 hours to complete

Clustering

In this section, you will learn about different clustering approaches. You learn how to use clustering for customer segmentation, grouping same vehicles, and also clustering of weather stations. You understand 3 main types of clustering, including Partitioned-based Clustering, Hierarchical Clustering, and Density-based Clustering.

...
6 videos (Total 41 min), 1 reading, 4 quizzes
6 videos
Intro to Hierarchical Clustering6m
More on Hierarchical Clustering5m
DBSCAN6m
1 reading
IBM Digital Badge2m
1 practice exercise
Clustering10m
4.7
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Top reviews from Machine Learning with Python

By RCFeb 7th 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

By AJJul 9th 2019

This was a very informative course. The videos provided a good background on the concepts and I found the labs especially helpful for learning to implement Python code for each technique covered.

Instructor

Avatar

SAEED AGHABOZORGI

Ph.D., Sr. Data Scientist
IBM Developer Skills Network

About IBM

IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame....

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Certificate, 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.

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