Sovelto Hybrid: Programming in Python for Data Science

Python is popular among developers due to its general applicability, extensive libraries, and large user community. Indeed, Python often works behind data science and big data solutions.

The Sovelto Hybrid learning program includes three online courses, supported by trainer-led webinars. The first online course takes you through the data science concepts and the basics of statistical functions using Excel. The second online course teaches you the Python programming language and environment. The third online course acquaints you with the use of Python in data analysis and with some of Python’s advanced features.

You will have access to the Microsoft Teams platform, which enables experiences and questions to be shared, and students to coach each other. The platform is managed by an experienced trainer. This means that you can enjoy both the freedom of self-study and the support of a learning community!

The learning program is suitable for data analysts and IT professionals who want to learn how to use the Python language to analyze data.

Schedule:

1. Kickoff

• Webinar 24 Sep, 15:00–16:30

1. Introduction to Data Science

• Self-study, 2 weeks (approx. 6 h/week)
• Webinar 5 Oct, 15:00–16:30

1. Introduction to Python for Data Science

• Self-study, 3 weeks (approx. 4 h/week)
• Webinar 26 Oct, 15:00–16:30

1. Programming with Python for Data Science

• Self-study, 4 weeks (approx. 8 h/week)
• Webinar 14 Dec, 15:00–16:30

Hybrid learning

In hybrid learning, you take online courses and have the support of online webinars held by an expert. After successfully completing the online course, you will receive a Microsoft certificate of completion. The course starts with a kickoff webinar that presents the outline of the program and the study methods, and gets you started with your studies. The program includes online sessions in which an expert teaches and illustrates course topics, which help you progress in your studies. The online courses include modules that are appropriately sized for completion in everyday life or alongside work. The modules include instructional videos, tests, links to additional materials, multiple-choice quizzes, and similar assignments, to ensure learning success.

The studies require you to be systematic and to work independently. You should, therefore, schedule the online sessions and the time needed for self-study in your calendar, to ensure that your studies progress on time.

What can you expect to learn?

Introduction to Data Science

• Basic data exploration and visualization techniques in Microsoft Excel
• Foundational statistics that can be used to analyze data

Introduction to Python for Data Science

• Explore Python language fundamentals, including basic syntax, variables, and types
• Create and manipulate regular Python lists
• Use functions and import packages
• Build Numpy arrays, and perform interesting calculations
• Create and customize plots on real data
• Supercharge your scripts with control flow, and get to know the Pandas DataFrame

Programming with Python for Data Science

• What machine learning is and the types of problems it is adept to solving
• How to represent raw data in a manner conducive to deriving valuable information
• How to use various data visualization techniques
• How to use principal component analysis and isomap intelligently to simplify your data
• How to apply supervised learning algorithms to your data, such as random forest and support vector classifier
• Concepts such as model selection, pipelining, and cross validation

Keywords: Data Science, Python