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Machine Learning Fundamentals with Python

Premium
IntermediateCourse

Unlock hidden insights and predict future trends with the power of machine learning! This dynamic Machine Learning Fundamentals with Python course equips you with all the essential tools to dive into both supervised and unsupervised learning, setting you up for success in the world of data-driven predictions.

Language

  • English

Topic

  • Machine Learning

Industries

  • Information Technology

Skills You Will Learn

  • Statistical Modeling, Random Forest Algorithm, Machine Learning, Algorithms, Unsupervised Learning, Python

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 13 hours

Platform

  • SkillsNetwork

Last Update

  • April 22, 2025
About this Course
Explore the world of Machine Learning (ML) with Python! This course is perfect whether you are looking to kickstart your journey into Machine Learning and Deep Learning or take your Data Science career to the next level.   

Course Overview 
In this comprehensive course, you'll dive into the core concepts of machine learning using Python, a widely used programming language. The course covers the distinction between supervised and unsupervised learning and examines the relationship between statistical modeling and machine learning. 
 
You will explore popular algorithms, including Classification, Regression, Clustering, and Dimensional Reduction, along with essential models like Train/Test Split, Root Mean Squared Error (RMSE), and Random Forests. Through practical, real-world examples, you'll see the societal impact of machine learning in ways you might not expect. 
 
Throughout the course, hands-on labs in Python will enable you to transform your theoretical knowledge into practical skills, applying machine learning techniques to solve problems. You'll gain confidence in using key algorithms and models, preparing you to apply machine learning in real-world scenarios.  
  
Enroll today and kickstart your data science career... You have a lot to look forward to!  

IBM Data Science Professional Certificate
This course is part of the IBM Data Science Professional Certificate. If you’re keen to kickstart a career in data scientist, we recommend you enroll for the full Professional Certificate program and work through the courses in order. Within just a few months, you’ll have job-ready skills and practical experience on your resume that will catch the eye of an employer! 
 
Course Syllabus 
Module 1 - Introduction to Machine Learning 
  • Introduction to Machine Learning 
  • Python for Machine Learning 
  • Supervised vs Unsupervised Learning 
Module 2 - Regression 
  • Introduction to Regression 
  • Simple Linear Regression 
  • Model Evaluation in Regression Models 
  • Evaluation Metrics in Regression Models 
  • Multiple Linear Regression 
  • Non-linear Regression 
Module 3 - Classification 
  • Introduction to Classification 
  • K-Nearest Neighbors 
  • Evaluation Metrics in Classification 
  • Introduction to Decision Trees 
  • Building Decision Trees 
  • Introduction to Logistic Regression 
  • Logistic Regression vs Linear Regression 
  • Logistic Regression Training 
  • Support Vector Machines 
Module 4 - Clustering 
  • Introduction to Clustering 
  • K-Means Clustering 
  • Hierarchical Clustering 
  • Density-Based Clustering 
Module 5 – Recommender Systems 
  • Introduction to Recommender Systems 
  • Content-based recommender systems 
  • Collaborative Filtering  
Module 6– Final Project 

What You'll Learn

  • Explain the difference between the two main types of machine learning methods: supervised and unsupervised 
  • Describe Supervised learning algorithms, including classification and regression 
  • Describe Unsupervised learning algorithms, including Clustering and Dimensionality Reduction 
  • Explain how statistical modelling relates to machine learning and how to compare them 
  • Discuss real-life examples of the different ways machine learning affects society 
  • Build a prediction model using classification 

Recommended Skills Before Taking this Course

A basic understanding of Python, along with knowledge of data analysis and visualization techniques, is required. Additionally, a minimum proficiency in high school-level mathematics is needed. 


Instructors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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Jeff Grossman

Founder, 617 Data Solutions Inc.

I create technical educational content and build stuff around data. I love kids, dogs, walking, bicycles and snow sports. I'm working on coming to terms with robots. I've been around long enough to witness an accelerating rate of change of technological advancement. We need all hands on deck to help protect ourselves from ourselves. Prosperity will come from efficiencies but will also require our acceptance of and cooperation with the change that is inevitable. Quoting Ray Kurzweil (via https://en.wikipedia.org/wiki/The_Singularity_Is_Near): "Kurzweil concedes that every technology carries with it the risk of misuse or abuse, from viruses and nanobots to out-of-control AI machines. He believes the only countermeasure is to invest in defensive technologies, for example by allowing new genetics and medical treatments, monitoring for dangerous pathogens, and creating limited moratoriums on certain technologies. As for artificial intelligence Kurzweil feels the best defense is to increase the "values of liberty, tolerance, and respect for knowledge and diversity" in society, because "the nonbiological intelligence will be embedded in our society and will reflect our values".

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IBM Skills Network

IBM Skills Network Team

At IBM Skills Network, we know how crucial it is for businesses, professionals, and students to build hands-on, job-ready skills quickly to stay competitive. Our courses are designed by experts who work at the forefront of technological innovation. With years of experience in fields like AI, software development, cybersecurity, data science, business management, and more, our instructors bring real-world insights and practical, hands-on learning to every module. Whether you're upskilling yourself or your team, we will equip you with the practical experience and future focused technical and business knowledge you need to succeed in today’s ever-evolving world.

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Abhishek Gagneja

Freelance Subject Matter Expert

I am a lifelong learner with more than a decade of teaching experience at university level. I am an AI enthusiast and love learning new things.

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