In-House Machine Learning Course for Programmers

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

Your team has got some programming experience?
They are still a stranger to data science and AI?
They are eager to get cracking ASAP?

We can co-create the course you're looking for!

About this course

Depending on your preferences, industry and team, we will teach your team everything they need to know to start creating their own data science models. These sessions will be given at your office or any other place you prefer.

To enroll in this course, your team is required to have a background in programming (preferably Python). If they do not, we recommend organising our in-house Data Science Course.

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.

+ Download Data Science Course Material

Most preferred program

(1 block - 3.5 hours, Dr. Denolf)

  • 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. Denolf)

  • 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.

(1 blocks - 3.5 hours, Dr. Josephy)

Summary techniques for data exploration

  • Data communication tips & tricks
  • Concise data visualisation and exploration using Python Seaborn & Matplotlib

(1 block - 3.5 hours, Dr. Josephy)

  • Inductive/predictive statistical modeling
  • Central Limit Theorem and estimation theory
  • Hypothesis testing with Analysis of Variance

(2 blocks - 7 hours, Sílvia C. Silva)

  • 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

(2 block - 7 hours, Grammens)

  • 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. De Baets)

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

We present the content you need. If you don't know what you need we are very happy to help you find out what your requirements are!

We garantee that you will get the most out of the time of your employees. Because we will make sure that the content is exactly what they need to start solving the challenges you are facing today.

If you have a specific challenge we can create tailored courses that help your team to solve the issue at hand.

Practical info

  • Dates: at your convenience
  • Duration: perfectly timed
  • Where: your place or somewhere else

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

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

Depending on the duration and location of the course, we can arrange coffee, juice, fruit and pastry every morning. And after a morning of heavy labor, we can provide lunch for everybody.

The price of this course may differ for every in-house company training depending on the amount of students, tailoring to the company, locations,... Let us know what you have in mind, and we will give you an offer.

All invoices need to be paid within 30 days after the date of the invoice.

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.

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

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. Participants who cannot make the revised date should follow the cancellation procedure above, with the difference that these participants will not be required to request cancellation 28 days before the course and will not 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

In-House Machine Learning Course for Programmers

  • Date / Period at your convenience
  • Location your place or elsewhere
  • Number of sessions the right amount
  • Session duration perfectly timed
  • Seats available as many as needed
  • Language English or Dutch
  • Price ask us and find out!

In-House Machine Learning Course for Programmers

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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
  • Strengthen 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

  • Jacob Denolf | Crunch Analytics

    Jacob Denolf

    Talent Lead / Senior 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.

  • Jelle Grammens | Crunch Analytics

    Jelle Grammens

    Senior Data Scientist

    Jelle is a skilled data scientist with a background in business and economics. He combines his knowledge of data analytics and machine learning with his business acumen to help customers bring their ideas to life.

  • Haeike Josephy | Crunch Analytics

    Haeike Josephy

    Senior Data Scientist

    Haeike started her career in physiology and evolutionary biology, but eventually transitioned towards studies in statistical data analysis. During her time teaching at Ghent University she obtained a PhD within that same field, with a particular focus on correlated data structures and causal inference. In her work, she greatly enjoys facing challenging puzzles that allow her to improve and explore, from one day to the next.

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