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Top 10 Courses and Specializations in February on Coursera

Posted in 'Top Courses' started by Carolyn, Mar 20, 2018.

  1. Carolyn

    Carolyn Founder at MoocLab Staff Member

    Gender:
    Female
    Location:
    Suffolk, UK
    Coursera have shared with us their top 10 Courses and Specializations based on the number of enrolments in February 2018.

    1. Deep Learning
    If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.
    • By Andrew Ng's deeplearning.ai
    • Specialization - 5 courses
    • Intermediate Specialization. Some related experience required.

    2. Data Science
    This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results.
    • By Johns Hopkins University
    • Specialization - 10 courses
    • Beginner Specialization. No prior experience required.

    3. Python for Everybody
    This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language.
    • By The University of Michigan
    • Specialization - 5 courses
    • Beginner Specialization. No prior experience required.

    4. Fundamentals of Accounting
    Accounting Basics for Managers and Entrepreneurs. Apply principles that underlie financial statements and facilitate business decisions and goals.

    • By the University of Illinois at Urbana-Champaign
    • Specialization - 5 courses
    • Beginner Specialization. No prior experience required.

    5. Machine Learning
    This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition.
    • By Stanford University
    • Taught by: Andrew Ng
    • 1 course

    6. Applied Data Science with Python
    The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language.
    • By the University of Michigan
    • Specialization - 5 courses
    • Intermediate Specialization. Some related experience required.

    7. Game Theory
    The course will provide the basics: representing games and strategies, the extensive form (which computer scientists call game trees), Bayesian games (modeling things like auctions), repeated and stochastic games, and more.
    • By Stanford University, The University of British Columbia
    • 1 course
    • Beginner level

    8. Investments I: Fundamentals of Performance Evaluation
    In this course, we will discuss fundamental principles of trading off risk and return, portfolio optimization, and security pricing.

    • By the University of Illinois at Urbana-Champaign
    • 1 course
    • Part of the iMBA offered by the University of Illinois

    9. Statistics with an R
    Master Statistics with R. Statistical mastery of data analysis including inference, modeling, and Bayesian approaches.
    • By Duke University
    • Specialization - 5 courses
    • Beginner Specialization. No prior experience required.

    10. Excel to MySQL: Analytic Techniques for Business
    In this Specialization, you’ll learn to frame business challenges as data questions. You’ll use powerful tools and methods such as Excel, Tableau, and MySQL to analyze data, create forecasts and models, design visualizations, and communicate your insights.

    • By Duke University
    • Specialization - 5 courses
    • Beginner Specialization. No prior experience required.
     
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