The profession of data scientist is one of the most sought-after in the 21st centruy. This part time online course from StackFuel will teach you how to use supervised and unsupervised machine learning algorithms, different data visualization methods and data storytelling so that you are able to take on the role of data scientist after you finish the course. You will develop the skills you need to work as a data scientist. You can then apply the knowledge you gained in your department and implement machine learning algorithms by yourself. During the course, you will work in our browser-based, interactive learning environment, the Data Lab. This is a full programming environment where you can execute code you write yourself.
Which starting date suites you best? You can choose between the following dates in the registration form:
24.08.20 - 07.02.21 | 12.10.20 - 28.03.21 | 23.11.20 - 09.05.21
- Data Wrangling: data processing with pandas and matplotlib, structured, semistructured and unstructured data, relational and NoSQL databases
- Machine Learning - algorithms at work: forecasts using Scikit-learn, supervised and unsupervised learning and it´s application, algorithms (Random Forests, Bayes Classification, Clustering)
- Inferential Statistics for Data Scientists: data queries, A/B testing with classical and Bayesian statistics
- Using Big Data the smart way: Hadoop infrastructure, data processing with the help of Spark
- The objective of the course is to understand and use performance metrics and assumptions from supervised and unsupervised learning models with sklearn.
- You will learn data storytelling principles as well as best practices for informative visualization design with bokeh algorithms from supervised and unsupervised learning, such as decision trees and random forests.
- theoretical input via online tutorials
- interactive exercises in our innovative Data Lab
- hands-on learning scenarios (industry business cases)
- work on your own Data Science project
- Suitable for anyone who wants to analyze data and make predictions based on this data in order to make data-driven decisions. You should be also be interested in machine learning.
- A good knowledge of Python and common modules (pandas, matplotlib) is required to participate in the Data Scientist Course.
- Standard = part-time online course to fit around your work (18 weeks)
- Certification: you will receive a certificate at the end of the course
- Browser-based training: you will have access to all the computing power you need to complete the course