Data science is developing at a rapid pace. This development has a major impact on the way in which organizations, both in the public and private sector, structure and execute processes. This impact can also be felt in relations with business partners, in decision-making and in terms of the competencies and skills that employees at every level of the organization must possess.
The Open University of The Netherlands has developed a challenging, hands-on training program for professionals, offering a mix of basic and advanced data science topics that will help you to prepare for the rapid (technological) developments in de field of data science and be part of it.
What’s in it for your organization?
Today, no business can afford to neglect data or fail to use it effectively for decision-making. It is becoming increasingly important to analyze what competitors are doing – big data gives you the answer to this. Big data is the future, so invest in the development of your employees’ technical data science skills, competencies and capabilities. After completing the training program, participants will be assessed by highly specialized experts and receive a certificate.
Voor wie is de opleiding bedoeld?
This program is especially designed for professionals looking to improve their technical data science skills and competencies. Some prior (technical) knowledge of programming and database structures is preferred. As this is an intensive training program given by a group of specialized experts who are at the forefront of the latest technological developments in data science and artificial Intelligence.
Courses and topics which are included in the program are listed below. A tailor-made program for group registrations or in-company training programs is also possible. Please contact Martine Hermans for more information.
Scientific Programming I and II
Roadmap, introduction to CRISP-DM methodology. Importance of programming in Data Science.
Fundamental concepts of programming and introduction to Python.
Databases, Data Formats, Data Transfer
Relational databases basics using SQL. Manipulate data and build queries across multiple tables. and On-Line Analytical Processing in relational databases. Json, MongoDB.
Data Understanding and data Preparation
Overview on data preparations techniques, (data cleaning, data binning, missing data, data inconsistencies), data structuring, data summarization, data statistics and basic reporting tools, hypothesis testing.
Data modelling using Machine Learning I, II, III
Canonical data mining tasks, data mining process, supervised and unsupervised data mining techniques, generalization of models, over fitting and model performance.
Data Modelling for Text Analytics I and II
Extracting information out of unstructured text, major techniques for analyzing and mining text.
Data Visualization in Python I and II
Fundamentals of data visualization and practice communicating with data. Design principles, human perception, color theory, and effective storytelling to encode and present data to an audience once an insight has been found. Matplotlib and Seaborn.
Time Series Analysis
Time series data, visualizing time series, identifying trends and seasonality, detrending and deseasonalizing in time series, forecasting using ARIMA and SARIMAX, statistic tests for stationarity and seasonality.
Deep Learning and Introduction to BDA
Within the deep learning module, we will go into detail on topics such as Backpropagation, Tensorflow + Keras, LSTMs, NLP, Convolutional Neural Networks for Text and Images. The last lecture will present an introduction to Big Data Analytics technologies in Python.
Our way of teaching
The program has been designed to help participants solve generic business problems and master a specific skill or competence, ensuring a constant relation between theory and practice. We also apply insights to generic or company specific cases and business challenges, and show how data science techniques can be used to improve innovation within your organization.
The program is offered online and consist of virtual meetings and independent learning in order to master all the topics that are discussed. The Open University is the leading part-time university in the Netherlands, specialized in personalized and interactive online education.
The virtual meetings will take place via yOUlearn, the online learning platform of the Open University. Each virtual meeting will take max. 2 hours.
We distinguish between virtual lectures and virtual lab session scheduled. The lectures will cover most of the theory behind the topics and concepts (including examples), which will end with and interactive discussion and/or Q&A. During lab sessions participants will put the theory into practice and work on exercises related to the discussed topics together. In between each session participants are expected to complete a number of independent learning tasks as well as tests / assignments which will be graded.
The working language throughout the program is English. All documentation/material is also written in English, including three books each participant will receive at the beginning of training program. Furthermore, participants will be taught, guided and supervised by English speaking OU experts.
Study load and training schedule
The study load of the complete course is approximately 280 hours. When following the complete program we advise participants to allocate approximately 10 hours per week to participate in live lectures, lab sessions and spend time on self-study tasks and tests. The complete program takes five months to complete. For tailor-made programs study load, set-up and planning may vary.
As a general recommendation, HBO (higher professional education) working or thinking level and/or several years of relevant work experience is advised. In addition, it is important that you are familiar with technical skills (such as programming skills / Python).
The Certified Professional Program Data Science (Python) is currently only available for group registrations or as (tailor-made) in-company program. Please contact Martine Hermans for more information.
For group registrations and in-company training programs, the participation fee per participant is depending on the set-up and number of participants. Please contact Martine Hermans for more information.
As from 1 January 2022 studiecosts are not deductible from your income tax anymore. Instead of this is
STAP-budget is a subsidy for workers and job seekers to follow a training, course or education to remain employable in job market. For more information please enter the website of rijksoverheid.nl.
The Lifelong Learning Credit (LLLK) discount scheme does not apply to Certified Professional Programs.
The Open University Course Fee Discount Scheme (KCOU) does not apply to Certified Professional Programs.
After successful completion of the full program participants will receive a Certified Professional Program (CPP) diploma from the Open University. The diploma (i.e. the acquired 10 ECTS) provides exemptions in the MBA Data Science and Digital Innovation of the Open University.
If you would like more information by mail, phone or Whatsapp about this specific program, or in case of a group registration or an in-company track please contact our Team Professional Programs by pushing the red button 'Contact' on this page.
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