In-House Data Science Course for Analysts
The world is changing fast for quantitative business analysts; the entire field is embracing the powerful tools offered by the world of machine learning and data science. This course will teach your team everything they need to know to master these new techniques!
Your team is no stranger to quantitative decision making?
They have got some data analytics experience?
They are convinced of the potential data science has to offer?
They are eager to get cracking ASAP?
We can co-create the course you're looking for!
Your profile
This example course is aimed at skilled analysts who are eager to expand their skill set. This means that participants should be comfortable with basic statics and mathematics, but more than anything you should be eager to learn!
- Have experience with traditional business intelligence tools to manipulate data (Excel, SAS, Google Sheets,...)
- Have an understanding of basic statistics and mathematics.
- Have a willingness to recap the material and train themselves, at their own pace.
Some programming or scripting experience will be helpful, but this is not required!
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.
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).
Unlike in the in-house Machine Learning Academy, your team does not need programming experience. This course includes a tutorial on programming and will help them through the technical side of Data Science at their own pace.
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)
- Introduction to Object Oriented Programming
- Python Data Types
- Python Flow Control
(1 blocks - 3.5 hours, Dr. Josephy)
- Matrix mathematics with Numpy
- Series & DataFrames with Pandas
- Data manipulation & wrangling
(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
(2 blocks - 7 hours, Dr. Denolf)
- Inductive/predictive statistical modeling
- Central Limit Theorem and estimation theory
- Hypothesis testing with Analysis of Variance
- Linear correlation analysis with linear regression
- Advanced linear regression with interaction
(2 blocks - 7 hours, Sílvia C. Silva)
- Basic concepts of machine learning and modeling
- Building, optimizing and testing machine learning models
- Regression (linear, logistic, ridge...)
- Clustering (K means)
- Classification (Support vector means, decision trees)
- Ensemble methods
(2 block - 7 hours, Dr. Denolf)
- Introduction to Natural Language Processing
- Introduction Neural Networks
- Overview of different layer architectures
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.
- Analyst
In-House Data Science Course for Analysts
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Date / Period at your convenience
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Location your place or elsewhere
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Number of sessions the right amount
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Session duration perfectly timed
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Seats available as many as needed
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Language English or Dutch
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Price ask us and find out!
In-House Data Science Course for Analysts
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Talk to you soon,
The Crunch Team
Why our clients choose us
Kurt Delaplace
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.
- Get a clear understanding of how Machine Learning works
- Improve products using Machine Learning
- Be able to lead your development team better
Thomas Mons
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!
- 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
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.
- 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
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.
- 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
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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.
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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.
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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.
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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.
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.