IBM
IBM Introduction to Machine Learning Specialization
IBM

IBM Introduction to Machine Learning Specialization

Learn machine learning through real use cases. Build the skills for a career in one of the most relevant fields of modern AI through hands-on projects and curriculum from IBM’s experts.

Xintong Li
Joseph Santarcangelo
Mark J Grover

Instructors: Xintong Li

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Get in-depth knowledge of a subject
4.7

(443 reviews)

Intermediate level
Some related experience required
2 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.7

(443 reviews)

Intermediate level
Some related experience required
2 months
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the potential applications of machine learning

  • Gain technical skills like SQL, machine learning modelling, supervised and unsupervised learning, regression, and classification.

  • Identify opportunities to leverage machine learning in your organization or career

  • Communicate findings from your machine learning projects to experts and non-experts

Details to know

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Taught in English

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from IBM
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Specialization - 4 course series

Exploratory Data Analysis for Machine Learning

Course 114 hours4.6 (2,190 ratings)

What you'll learn

Skills you'll gain

Category: Data Cleansing
Category: Statistical Inference
Category: Feature Engineering
Category: Exploratory Data Analysis
Category: Machine Learning
Category: Artificial Intelligence
Category: Data Analysis
Category: Pandas (Python Package)
Category: Data Quality
Category: Data Presentation
Category: Data Access
Category: Statistical Analysis
Category: Big Data
Category: Probability & Statistics
Category: Data Manipulation
Category: Data Transformation
Category: Jupyter
Category: Statistical Hypothesis Testing

Supervised Machine Learning: Regression

Course 220 hours4.7 (722 ratings)

What you'll learn

Skills you'll gain

Category: Regression Analysis
Category: Supervised Learning
Category: Scikit Learn (Machine Learning Library)
Category: Machine Learning
Category: Applied Machine Learning
Category: Data Processing
Category: Feature Engineering
Category: Dimensionality Reduction
Category: Pandas (Python Package)
Category: Statistical Modeling
Category: Data Manipulation
Category: Classification And Regression Tree (CART)
Category: Predictive Modeling
Category: Performance Metric

Supervised Machine Learning: Classification

Course 325 hours4.8 (404 ratings)

What you'll learn

Skills you'll gain

Category: Supervised Learning
Category: Machine Learning Algorithms
Category: Machine Learning
Category: Performance Metric
Category: Applied Machine Learning
Category: Statistical Modeling
Category: Feature Engineering
Category: Regression Analysis
Category: Sampling (Statistics)
Category: Predictive Modeling
Category: Classification And Regression Tree (CART)
Category: Data Cleansing
Category: Data Processing
Category: Scikit Learn (Machine Learning Library)

Unsupervised Machine Learning

Course 423 hours4.7 (307 ratings)

What you'll learn

Skills you'll gain

Category: Unsupervised Learning
Category: Dimensionality Reduction
Category: Machine Learning Algorithms
Category: Data Analysis
Category: Natural Language Processing
Category: Unstructured Data
Category: Big Data
Category: Feature Engineering
Category: Statistical Machine Learning
Category: NumPy
Category: Data Science
Category: Scikit Learn (Machine Learning Library)
Category: Machine Learning
Category: Data Mining
Category: Linear Algebra
Category: Text Mining

Instructors

Xintong Li
IBM
2 Courses51,757 learners

Offered by

IBM

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