Applied Data Science: Machine Learning
This online program, delivered by one of the most prestigious universities in the world, 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 have a solid foundation in working with the entire data pipeline.
Who is the target audience?
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. Switch careers or open up new career opportunities in your current workplace with a formal recognition of your skills and an EPFL certification.
Why should you enroll?
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.
Join a free class
Join us for a complimentary online session where we will provide 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.
Course Curriculum
The 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 neighbours
- 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
- Your opportunity to showcase your data science and machine learning skills
- Work on the full data science pipeline of a real-life project
- You choose the topic and the project. Your capstone project can be about your passion or relevant to your job
- Non-disclosure agreements available on request for sensitive or confidential data sets
Examples of capstone projects
Previous examples of impactful projects using real-life datasets include:
- Neuroscience – Human brain activity prediction
- Medical – Lung cancer detection on clinical X-ray images
- Research – Prognostic and diagnostic analysis of Covid-19 data
- Politics – Swiss political orientation prediction
- Oil & Energy – News headlines analysis
- Environment & sustainability – Ozone-level forecasting
- Finance – Short-term prediction of stock market or cryptocurrencies
Online Learning Experience
There’s never been a better time to learn online. Gain access to EPFL’s world-class continuing education programs tailored to your needs from anywhere in the world.
Learn online, Learn at your pace
This course consists of approximately 450 hours of learning material, instructor led coaching and hands-on project work.
There are no fixed start dates and you can learn at your own pace online (no onsite presence required).
Job-ready skills with an EPFL Diploma
The course equips learners with real-world applicable skills commonly sought by employers looking to recruit Data Science experts. During their capstone project, learners have the opportunity to showcase their new skill-set as they work on the full data science pipeline of a real-life project. All graduates will earn an EPFL Diploma and 15 ECTS credits.
Personalized support and coaching
Each subscription provides 24/7 access to our own learning platform and includes:
- weekly one to one video coaching sessions with EPFL instructors
- Q&A forum managed by EPFL instructors
- personalized feedback on your assignments
Interested in learning more about our programs?
FAQ
This program is taught at an intermediate level. You should have the following tools, skills and abilities prior to registering for this course:
- English at B2 level
- 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
The monthly subscription fee is CHF 490.-
Please contact us if you would like to request a quote or to pay a flat fee for the duration of the course: [email protected]
The course is estimated at 450 hours. This includes all project work. Your completion time will depend on how much time you can dedicate to your learning experience each day/week/month.
All of our programs consist of video training, written lessons and hands-on exercises. The curriculum is based on hands-on project work. The course projects provide the opportunity to demonstrate that you have acquired the skills taught in the program.
Our courses and programs are all self-paced; you can start learning immediately. Create your learner account using the link below to get the ball rolling:
https://learn.extensionschool.ch/sign_up
Please note that we reserve the right to limit the number of enrollments at any given time to ensure that our course instructors can provide the high-quality and personalized support that each of our learners deserve. You will be informed about the next available start date if this is the case.
You’ll be taken to our secure enrollment site, where you will need to provide the following information:
- Personal information including your name, current address and date of birth;
- Valid credit card details;
- Valid form of government-issued, photo ID that matches your registration name. In general, we accept passports and driver’s licenses.
Ready to start learning?