Online Course – IBM Certified Professional Specialization in Machine Learning

Learn about machine learning through practical cases. Acquire the skills required for a career in one of the most relevant areas of modern artificial intelligence through practical, knowledgeable projects from IBM professionals.

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קורס אונליין - התמחות מקצועית מוסמכת בלמידת מכונה של IBM

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Identify the potential of machine learning and artificial intelligence algorithms in various business situations.
  • Distinguish when to use machine learning to explain behaviors and when to predict future outcomes.
  • Evaluate your machine learning models and improve your skills with best practices.
  • Develop analytical skills in the field of machine learning.
  • Communicate insights using data analysis skills.
  • Prepare a final presentation to communicate the insights with colleagues.

What you will learn in the course

Courses for which the course is suitable

  • Machine Learning Engineer
  • Data Scientist
  • Data Analyst
  • Algorithm developer
  • Artificial Intelligence Expert
  • Machine Learning Project Manager
  • Data Technology Consultant
  • Software developer with a specialization in machine learning
  • Data scientist
  • Information Systems Analyst

Internship – a four-part course series

Machine learning skills are becoming increasingly important in the modern job market. In 2019, machine learning engineers were ranked number one in the United States, with a 344% increase in job opportunities in the field between 2015 and 2018, and an average base salary of $146,085.

This four-part course series will help you acquire the foundational skills for success in a sought-after career in data learning and science. Upon completion of the program, you will be able to:

  • Identify the potential of machine learning and artificial intelligence algorithms in various business situations.
  • Distinguish when to use machine learning to explain behaviors and when to predict future outcomes.
  • Evaluate your machine learning models and improve your skills with best practices.

Upon completion of the program, you will develop real-world machine learning skills to use in your job or job search, as well as a portfolio of projects that demonstrate your expertise. You will also receive a Coursera certificate and an IBM badge to share your achievements with your network and potential employers.

Applied learning project

Throughout the program, you will complete hands-on projects designed to develop your analytical and machine learning skills. You will explain your insights from each project using data analysis skills, including preparing a final presentation to communicate your insights with peers in the machine learning field.

It is recommended that you collect the projects you have completed into an active online portfolio that showcases the skills learned in this internship.

Details of the courses that make up the specialization

Machine Learning Courses

Course 1: Exploratory Data Analysis

Duration: 14 hours
Rating: 4.6 (1,876 ratings)

What you’ll learn

  • Collect data from various sources: SQL, NoSQL, APIs, cloud
  • Feature selection techniques and feature engineering
  • Handling categorical and ordinal properties
  • Detection and treatment of extreme situations
  • Understanding the importance of the reed feature and applying different reed techniques

Skills you will acquire

  • Artificial Intelligence (AI)
  • Machine learning
  • Feature engineering
  • Statistical hypothesis testing
  • Researcher Data Analysis

Course 2: Supervised Machine Learning: Regression

Duration: 20 hours
Rating: 4.7 (584 ratings)

What you’ll learn

  • Training regression models to predict continuous outcomes
  • Using error measures to compare models
  • Best practices: training and testing divisions, regulatory techniques

Skills you will acquire

  • Linear regression
  • Machine Learning (ML) Algorithms
  • Regression regulation: Ridge, LASSO

Course 3: Supervised Machine Learning: Classification

Duration: 24 hours
Rating: 4.8 (354 ratings)

What you’ll learn

  • Training predictive models to classify categorical outcomes
  • Best practices for classification
  • Handling data sets with unbalanced classes

Skills you will acquire

  • Unified Learning
  • Classification algorithms
  • Decision tree

Course 4: Unsupervised Machine Learning

Duration: 23 hours
Rating: 4.7 (258 ratings)

What you’ll learn

  • Finding insights from data without a destination
  • Clustering and Dimension Reduction Algorithms
  • Best practices for unsupervised learning

Skills you will acquire

  • Kibbutz analysis
  • Dimension reduction
  • Kibbutz K Means

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