Data Science & Machine Learning

Master the skills and techniques used by real data scientists in the tech Industry, including Python code in this Data Science and Machine Learning Course.

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Course Highlights

  • Includes 68 lectures and 9 hours of video content.
  • Learn how to perform machine learning on "big data" using Apache Spark and its MLLib package.
  • Apply best practices in cleaning and preparing your data prior to analysis
  • Be able to design experiments and interpret the results of A/B tests
  • Suitable for software developers or programmers who want to transition into the data science career path.

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Certificate of Completion

Data Science & Machine Learning
Frank K.
Frank Kane
Course Tutor

Of Course is part of Be-a Education Ltd, a UK Registered Learning Provider
(UKPRN: 10064410) Company No 08761384

  • Enrol and become certified in a new skill
  • Share your new skill with employers, friends and colleagues
  • Build a porfolio of course projects
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Course Facts

Course requirements There are no prerequisites for this course.

Course Teacher

Frank Kane

Data Miner and Software Engineer

More Info

This course will teach you the techniques used by real data scientists in the tech industry and prepare you for a move into this career path. It includes hands-on Python code examples which you can use for reference and for practice. It also contains an entire section on machine learning with Apache Spark, which lets you scale up these techniques to "big data" analysed on a computing cluster.

Frank Kane spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to millions of customers. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. He also started his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.

This course is intended for software developers or programmers who want to transition into the lucrative data science career path. It would also suit Data analysts in the finance or other non-tech industries who want to transition into the tech industry. You will learn how to analyse data using code instead of tools and it covers the machine learning and data mining techniques real employers are looking for.