Python is going to be in year 2021 the most widely used programming languages in the world. Of its applications, data analysis, data science and machine learning are the most growing. Python has also already overtaken the R language in its popularity.
Python includes important data processing tools such as pandas and numpy, which are even talked about as a replacement for Excel. These tools are widely used in many companies to bring more competitiveness and enable the use of Big Data. Some of these companies are Nordea, Netflix, Amazon, and IBM.
The basic philosophy of Python is to make programming as simple, beautiful and easy as possible. Python is easy to access and has been widely used in teaching teaching in the university world.
This course is best suited for people who are beginners and have some experience in programming or no programming experiences yet but like challenges.
The trainer is Jari Jaanto, M.Sc. (Tech). Jaanto has extensive experience in large data sets, programming languages, databases, cloud services, software development and data analysis.
The course structure:
In this course, we will go through the basics of Python during the first day using the Microsoft Azure cloud service. During the day, you will learn how to program and get tools to expand your skills independently. You will be able to effectively search for information on how to extend your Python programs and use Python’s rich libraries.
During the second day, we will review the Python data analysis libraries and process the data. You will learn the basics of data analysis and get to solve real world problems.
Day 1:
- What is a python?
- History + Versions
- Basic concepts (syntax, conditionals, loops)
- Running Python code in a Microsoft Azure environment
- Data types and data structures
- Functions and definition of functions
- Math & Random
Day 2:
- Data Analysis Libraries: Numpy, Pandas
- Reading and writing from Excel
- Reading and writing to SQL database
- Data preparation
- Data analysis
- Visualization
- Accessing Azure resources
- Additional tasks: Object-oriented programming, Functional programming, ML
