Camille Van Hoffelen

Camille Van Hoffelen

Lead Teacher

Advanced
6 weeks part time

Modern Deep Learning

Next training: January 2022

Join a 6-week training to take your applied and theoretical Deep Learning skills to the next level.

Keep up with the state-of-the-art to lead experiments and discussions in your Machine Learning team.

Part-time course compatible with your full-time job.

Learn more
Data Science Course Syllabus

Learn Deep Learning

  • 👋 Who is this for

    This course is perfect for the Machine Learning student moving past basics, the Software Engineer looking to specialise in Deep Learning, or the Data Scientist trying to keep up with the state-of-the-art.
  • 📚 Requirements

    Beginner Data Science skills are required. Students should be comfortable with python, jupyter notebook, and NumPy, Pandas, SciKit-Learn libraries. Basic understand of Machine Learning theory (what's logistic regression?) and practice (how to measure model accuracy?) are also needed.

Detailed course program

You will learn to wrestle with Deep Learning (DL) methods, and make Neural Networks (NNs) reveal all their secrets.

  • First, you will build strong theoretical foundations by building NNs from scratch with pytorch.
  • Then, you will deal with the hands-on challenges of DL: debugging in pytorch, and applying modern optimisation and regularisation methods to ensure successful NN training.
  • Next, you will explore state-of-the-art model architectures & learning paradigms by delving into DL's most popular applications.
  • With Computer Vision, you will build Convolutional Neural Networks, Generative Adversarial Networks, and discover the power of Transfer Learning. With Natural Language Processing, you will convert words and sentences into vectors, train transformers, and generate text. Then, you will expand your applications with time series modelling, sequence-to-sequence learning, and imitation learning for knowledge graphs.
  • Finally, the final project will reinforce these skills and allow to focus on one state-of-the-art paper which you will implement and train on a public dataset.
Data Science Course Syllabus

Week 1

Neural Network Basics

Explore Neural Network theory from scratch, and put it into practice with Pytorch.

Week 2

Neural Networks Training

Deep dive into Neural Network optimisation and regularisation methods, and debug common training issues in pytorch.

Week 3

Computer Vision

Deep Learning methods applied to image data: learn about CNNs, understand the transfer learning revolution, and discover generative models.

Week 4

Natural Language Processing

Deep Learning methods applied to text data: learn feature representations of symbolic sequences, tackle the almighty transformer, and experiment with generative language models.

Week 5

Sequences and Graphs

The best of the rest: apply sequence models to time series data, explore the seq2seq paradigm, and tackle imitation learning with knowledge graphs.

Week 6

Final project

This chapter tests your skills by implementing a state-of-the-art Deep Learning model from literature, and training it on a public dataset.

Camille Van Hoffelen

Meet Your Teacher

Camille Van Hoffelen

Camille has worked as a Machine Learning Engineer for the last 7 years (Seal, DocuSign...), with a focus on large scale Natural Language Processing systems.

Camille graduated with an MSci in Physics from Imperial College London, before catching the data science bug and diving into legal AI with Seal Software, later acquired by Docusign.

He was a lecturer in Machine Learning at Ilia State University, and remains an avid presenter at meetups and hackathons around Europe.

Camille is currently the CTO & Co-founder of Watergenics, where he strives to build a sustainable future for our blue Planet by augmenting water quality sensors with AI.

Modern Deep Learning

3 seats left

1900€

Next training: January 2022

Enroll & start learning

What's included in the live course:

  • Part-time training
  • Join a micro-class of < 10 students
  • Compatible with your full-time job
  • 3 hours of live interactive class per week
  • 3 to 5 hours of coding exercises per week
  • Demo day & certification of course completion
  • Connect with other students and learn together
  • Master the latest tools & languages in machine learning
  • 1:1 calls with the teachers
  • 5-day free trial
  • Eligible to CPF financing in France 🇫🇷

Drop us a line

We'd be happy to answer your questions, and check together if the program is a good fit for you.

Meet the community

Alumni, students & teachers are the heartbeat of the Jungle Program community.
Graduates are data scientists, machine learning engineers, full-stack developers and CTO of startups.

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Frequently Asked Questions

Financing & Payment

The is a part-time online course that can be done entirely from your home or office. The price is 1900 € tax included.
Yes, we are flexible with the payment plans. Please contact us via the chat to discuss the payment options we have available.
It’s with great pleasure that we announce Jungle Program is an official CPF-Eligible training.
Yes. Take a free 5-day trial. You will not pay anything unless you decide to continue.

Course

You will take part in a 1.5-hour course, every Monday and Wednesday, and receive the full support of our expert trainer. You will experience a total of 36 hours of training including 18 hours of hands-on coaching with our expert professors.
Yes, our online courses are created for anyone with a full-time job. You can take your training in your spare time.
We offer you the mentorship you need to take your career to the next level. We’ll stay in touch and guide you throughout your career, no matter where it takes you.
Every week, you’ll be given a set of hands-on homework assignments that will guide your growth. You will have the opportunity to show your skills, knowledge and expertise through exercices, a final project, and an evaluation by our team of teachers. Upon completion, you will become a Jungle Program Certified Data Scientist.