Deepen

Applied Data Science:
Machine Learning

  • 450 hours
  • 490 CHF / month
  • EPFL Diploma

This intermediate-level program will give you hands-on experience in one of the hottest areas of data science. You’ll learn the techniques and tools for data acquisition, transformation and predictive analysis, ensuring you having a solid foundation in working with the entire data pipeline.

EPFL Extension School learner

Ready to start learning?

Download the course brochure

Join our Discovery Webinar

This complimentary online session will be a high-level overview of how to use machine learning to solve problems, make decisions and build smart programs, including an overview of the online courses available to gain these sought-after skills.

Join our next session

Why you should take
this course

From Siri to smart cars, the ability to make computers learn from data without being programmed to do so is reshaping the modern world—making it a highly sought-after skill across industries.

Machine Learning
is growing rapidly

As one of the fastest-growing fields in data science, machine learning is increasingly used to make high-level decisions and develop innovative new technologies. It’s why there are 50% more jobs requiring machine learning skills than job seekers who have them. It’s also the 3rd highest paid analytical skill.

Machine learning is
disrupting every sector

  • Diagnostics
  • Marketing & content
  • Financial trading
  • Optimizing inventory
  • Screening & security

Meet Panagiota
—Course Developer
and Instructor

Photo of Panagiota Xydi, Course Instructor

Panagiota’s life could have taken many different courses. But she’d always loved science and making things. After graduating in physics, she embarked on a scientific career, first at the world-famous CERN and then in nuclear safety in Paris.

Along the way, she acquired a passion for coding and its problem-solving abilities and a decision to change careers. Self-taught in python, she took the Applied Data Science: Machine Learning course while pregnant with her first child. It proved to be a decisive step that led to a job at the EPFL Extension School. It tapped into her ability to communicate and share learning in alternative ways to people without technical backgrounds. Describing Machine Learning as “food for the brain”, she says it is the must-have skill for the future. Much like coding has been.

Panagiota Xydi is a former learner at the EPFL Extension School where she is now a Course Instructor.

Who is it for?

Photo of the EPFL campus

Applied Data Science: Machine Learning is for anyone who wants to gain the skills and understanding to oversee or implement a project that covers the full data science pipeline, including modelling and evaluation. You either want to switch careers or open up new career opportunities in your current workplace with a formal recognition of your skills and an EPFL certification.

" The course structure and content are amazing. You cannot find anything else like it online. "

Pascal, EPFL Extension School Alumnus

Program curriculum

The Applied Data Science: Machine Learning program includes four certified courses and a customizable capstone project. Learners who successfully complete the program earn an EPFL Certificate of Open Studies Diploma and 15 ECTS credits.

01. Introduction to Data Analysis with Python

Foundational concepts of data analysis:

  • Getting started with Python
  • Explore your first data set
  • The Jupyter notebook
  • A first look at NumPy & Pandas
  • The basics of data visualization
  • Probability for data science
  • Linear algebra for data science
02. Applied Data Analysis

Working across the entire data analysis pipeline

  • Getting, cleaning & manipulating the data
  • In-depth NumPy & Pandas
  • Working with textual data
  • Working with time-series data
  • Databases in Python
  • Statistical data analysis
03. Applied Machine Learning 1

Basics of machine learning with Scikit-learn

  • Introduction to machine learning
  • Fitting a first model
  • Cost functions & outliers
  • Linear regressions
  • Gradient descent
  • Feature engineering
  • Regularization
04. Applied Machine Learning 2

Advanced machine learning techniques

  • K-nearest neighbors
  • Bias-variance trade-off
  • Logistic regressions
  • Decision trees & SVMs
  • Clustering & dimensionality reduction
  • Introduction to deep learning
  • Convolutional neural networks
  • Machine learning with different data types
05. Capstone Project

Showcase the skills and knowledge you’ve learnt on the program by applying them to your own data science project.

These program details are subject to change; please refer to the program outline at the time of registration.

Prerequisites

This program is taught at intermediate-level. You should have the following tools, skills and abilities prior to registering for this course:

  • English at B2 level
  • A computer with a webcam, microphone and a minimum internet connection of 2Mbps download / 512kbps upload, enabling you to stream videos with sound and to effectively participate in video chats
  • Basic understanding of algebra, geometry, calculus (derivatives), probability and statistics
  • Familiarity with computer environments (what is a program, file system, file formats, terminal, programming language library)
  • Prior experience with any programming language

Your course instructor team

Amir Khalilzadeh
Amir Khalilzadeh Course Developer and Instructor
Christian Luebbe
Christian Luebbe Course Developer and Instructor
Panagiota Xydi
Panagiota Xydi Course Developer and Instructor

What you'll
get from us

  • 100% online
  • Hands-on project work
  • One-to-one personalized support
  • Self-paced learning
  • World-class EPFL quality
  • Real-world, job-ready, applicable skills

Ready to start learning?

Applied Data Science: Machine Learning

  • 450 hours
  • 490 CHF / month
  • EPFL Diploma
Enroll now

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