The Machine Learning Academy

Learn the tools and techniques of Machine Learning so you can implement Data Science in your day-to-day job and create new opportunities for your company.

You've got some programming experience?
You're still a stranger to data science and AI?
Your're eager to get cracking ASAP? 

This is the course you're looking for!

About this course


Five full days of training, spread across five weeks will teach you everything you need to know to start creating your own data science models. These sessions will be given at the Co.Station in Ghent, the home turf of the Crunch Analytics team. 

The workshops consist of presentations given by machine learning experts, these presentations are followed by hands-on training exercises using interactive browser based notebooks (Jupyter, Python). 

This course is focused on letting the student acquire practical skills, rather than an abstract theoretical course. 

Program

(1 block - 3.5 hours, Dr. Kerkhove)

  • Data science 101
  • The core concepts of the data science world
  • Moving from descriptive to diagnostic, predictive and finally prescriptive analytics

(1 block - 3.5 hours, Dr. Kerkhove)

  • Python Programming basics (data types, logical & conditional processing)
  • Python Numpy and Pandas modules
  • Data manipulation and wrangling in Python

Note: if you are already highly experienced with python you might get through this session somewhat quicker than the rest. The materials covered in this part enable everyone to take part in the subsequent sessions, regardless of their background. 

(2 blocks - 7 hours, Dr. Denolf)

  • Concise data visualisation and exploration using Python Seaborn & Bokeh
  • Descriptive and exploratory statistics
  • Inductive/predictive statistical modeling
  • Hypothesis testing

(2 blocks - 7 hours, Dr. Denolf)

  • Basic concepts of machine learning and modeling
  • Building, optimizing and testing machine learning models
  1. Regression (linear, logistic, ridge...)
  2. Clustering (K means)
  3. Classification (Support vector means, decision trees)
  4. Ensemble methods

(1 block - 3.5 hours, Dr. Kerkhove)

  • Data housekeeping tricks & tips
  • Deploying data pipelines
  • Sanity checks & stress tests

(1 block - 3.5 hours, Dr. Kerkhove)

  • Introduction to the possibilities of NLP
  • Basic feature extraction using Sklearn (bag of words, TF-IDF,...)
  • Advanced feature extraction using NLTK (stemming, lemmatization, N-grams,...)
  • Creating predictive models using NLP

(2 blocks - 7 hours, Dr. Denolf)

  • Introduction to Neural networks
  • Deep learning neural networks with Keras
  • Introduction to Tensorflow
  • Image Recognition with convolutional neural networks

Practical info

  • Dates: fri 20/04, fri 27/04, fri 04/05, fri 18/05, fri 25/05
  • Duration: 9:00 - 12:30 and 13:30 - 17:00
  • Where: Oktrooiplein 1 - 9000 Ghent, Belgium

This course requires you to bring your own laptop, some pointers: 

  • An OS X or Linux machine will make your life easier, but we can make it work on Windows
  • We're doing some heavy computing, bring your charger
  • Make sure you have sufficient permissions to install things on your laptop (i.e. administrator rights)

Every morning there will be coffee, juice, fruit and pastry.

The course will take place in the Quantum building at Dampoort Ghent on the first floor. It is easily accessible by bus and train since the railway station is only a 5 minute walk.

There are plenty of free parking spaces in the Afrikalaan (5 min walk), or if you want to park up close the parking of the Dampoort station is the best choice. If you're coming by bike there are plenty of bicycle racks at the side of the Quantum building (near the water). 

Payment must be received in full prior to the course start date. You must pay each invoice we issue within 30 days starting from the date issued. 

All cancellations must be received in writing (email is acceptable) 28 calendar days before the start of the course and will be subject to an administration fee of 50 EUR (excl. BTW). Cancellations made after this date will be charged the full course registration fee.

Registrants who do not attend on the day will be considered ‘no shows’ and will be charged the full course registration fee.

Confirmation of your booking will be emailed to you on receipt of your booking. 

Crunch Analytics will not be held liable for any transport or accommodation costs in the unlikely event of a course being cancelled.

Please note, due to circumstances beyond Crunch’s control, speakers, venue and timings may vary. 

Crunch Analytics reserves the right to cancel or re-schedule the event if necessary. In the case of cancellation by Crunch Analytics a full refund of course fees will be made. In the event of a re-schedule course fees will be transferred to the new date. Delegates who cannot make the revised date should follow the cancellation or delegate substitution procedures above, delegates will not be required to request cancellation 28 days before the course if the new date makes this impossible, nor will they be charged the 50 EUR administration fee. 

Acquired competences

Basic data types, as well as using numpy and pandas to wrangle data in Python. 

Perform state-of-the-art explanatory and predictive statistical analytics in Python.

Construct your own machine learning and AI models in Python, tailored and tuned to your specific business setting.

Sklearn rightfully is one of the most popular packages to create data science models, after these sessions you will be sufficiently proficient to use this package. 

Knowing what constitutes a predictive model, using different models for different challenges, knowing the lingo of a datascientist,...

Obtain insights and intuitions in the inner mathematical methods behind these applications.

Use these understandings to easily apply machine learning techniques in other programming languages

Build a solid theoretical foundation allowing you to master new developments and techniques in this fast evolving field

Use your modeling techniques to successfully solve business intelligence questions.

These courses go beyond the mere basics, making sure that when you've finished these sessions you know how to start with deep learning, natural language processing and even setting up data pipelines for model deployment. 

Learn how to communicate your results to your fellow co-workers, elevating the data insights across your company and be able to follow specialised media, blogposts and papers. 

After the course you will also become a part of the data science community! Where you will be able to ask questions to your peers and mentors of the academy.

  • Programmer

The Machine Learning Academy

  • Date / Period 20 April - 25 May 2018
  • Location Ghent - Belgium
  • Number of sessions 5
  • Session duration 9:00 - 12:30 & 13:30 - 17:00
  • Seats available 15
  • Language English
  • Price € 1.500 pp. excl. BTW (Early Bird until 22/02)

The Machine Learning Academy

Great that you are showing interest in the Machine Learning Academy! Fill in this form to subscribe or ask questions. We'll get back to you as soon as possible with the answers and specifics. 

Talk to you soon, 

The Crunch Team

Why our clients choose us

Kurt Delaplace | Crunch Analytics

Kurt Delaplace

Team Lead, In The Pocket

I wanted to have a better understanding of Machine Learning, to enable me to spot the opportunities to use this new technology within my projects. Participating in the sessions by Crunch Analytics has helped me to guide my team in the right direction, and improve the way we build applications. 

Why choose Crunch?
  • Get a clear understanding of how Machine Learning works
  • Improve products using Machine Learning
  • Be able to lead your development team better
Thomas Mons | Crunch Analytics

Thomas Mons

Director of Engineering, In The Pocket

Our goal is create digital products that make people happy and makes businesses grow. Within 3 years all digital products will contain some form of artificial intelligence. Hence, it is essential for us to keep up with these technologies!

Why choose Crunch?
  • Embrace the shift towards Artificial Intelligence to stay relevant to users
  • Build the ability to identify Machine Learning opportunities
  • Strenghten and maintain human capital
Michael Warner | Crunch Analytics

Michael Warner

Integrations Engineer, Showpad

Like many other companies Showpad has not remained blind to the opportunities offered by data science and machine learning. My participation in these sessions has allowed me to apply machine-learning tools and techniques in my day-to-day job, moving closer to a role as a fully fledged data scientist. 

Why choose Crunch?
  • Full hands-on materials, examples and notebooks you can keep for later
  • Perfect pace, not too fast nor too slow, straight to the point
  • Learn from very knowledgeable mentors, always available to answer questions and help out wherever possible
Kerensa Tiberghien | Crunch Analytics

Kerensa Tiberghien

Clinical Data Scientist, MoveUP

At moveUP we are moving from expert-driven to data-driven predictions to offer the best suited rehabilitation therapy for each our patients. Participating in these training sessions was the ideal way for me to acquire better insight into to possibilities offered by machine learning within this context

Why choose Crunch?
  • Gain the necessary insights to prepare for your data science project
  • Ask and discuss your challenges with the mentors
  • Hands-on training means you will be able to really apply Machine Learning afterwards

Your teachers

  • Louis-Philippe Kerkhove | Crunch Analytics

    Louis-Philippe Kerkhove

    Co-Founder and Head of Analytics

    Louis-Philippe started out in business and economics, but quickly developed a passion for algorithmic and mathematical problem solving. After spending time in academia - and earning his PhD in 2016 – he is now leading the analytics team at Crunch Analytics, applying this knowledge to solve real business problems using cutting edge tools and techniques. 

  • Jacob Denolf | Crunch Analytics

    Jacob Denolf

    Data Scientist

    Jacob started his career in theoretical mathematics, but switched towards the applied side, getting a PhD at the department of data analysis. With a deep passion for analytics he now immerses himself in training future data scientists and making the data dreams of our clients a reality.

In-house Company Training

Do you want one of these courses given privately at your company? Or do you have a specific training in mind but you can’t find it here? Talk to us and we’ll discuss it further.

Interested in how you can use data to make an impact?

contact us