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Machine Learning with Python, IBM

4.7
748 ratings
85 reviews

About this Course

This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed! By just putting in a few hours a week for the next few weeks, this is what you’ll get. 1) New skills to add to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 2) New projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more. 3) And a certificate in machine learning to prove your competency, and share it anywhere you like online or offline, such as LinkedIn profiles and social media. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Top reviews

By RC

Feb 07, 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 JJ

Dec 06, 2018

I am happy to have this online education, I drop out my nuclear engineering degree, I am happy to learn practical things with future... I work for IBM also...but I want to become a data scientis

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85 Reviews

By Samir Shah

Feb 15, 2019

Fantastic course! Only thing given the level of detail contained herein, is to consider splitting this into part 1 and 2 so can more fully capture the essentials.

By Dhiraj Kumar Pandit

Feb 15, 2019

Perfect Course

By Varun Vijaywargi

Feb 13, 2019

This course is definitely not for starters. People should have good knowledge before enrolling in this course and then this can be taken as an excellent refreshing course.

By Ata Mustafa

Feb 13, 2019

nice job!

By Abhishek Reddy DV

Feb 11, 2019

Very good content

By Michael Golden

Feb 10, 2019

Excellent course. The course pace, clarity of instructors, and training content are all top-of-the-line. Thank you!

By Prakash Rajendiran

Feb 10, 2019

This course helps me to get understand about Machine Learning.

By piyush gupta

Feb 08, 2019

Though this course is a good introduction to machine learning concepts, but i believe it was a little superficial about the inner working of the core concepts( evades the relevant mathematics on many occasions).

What you will learn: An overview of the working of various elementary ML algorithms from data wrangling to implementation.

What you won't learn: The maths behind various learning techniques.

Suggestions to improve: Implementation of the Algorithms from scratch, emphasizing the mathematical background of each technique would help a lot to the first time learner, though it might narrow down the target audience a bit, but would be much beneficial to those who are willing to put some extra hours to brush up those requirements at their own end.

By Chris Green

Feb 08, 2019

Excellent exposure to various Machine Learning approaches.

By Radhika Kannan

Feb 07, 2019

The course concentrates more on Maths rather than explaining how algorithm can be implemented in Python. This is difficult for a someone with less knowledge in Maths.

The lab exercises when compared to rest of the course is not satisfactory because in lab sessions, the algorithms were not explained and lacks Student excercise. It also lacks clarity around when to use which algorithm.