Introduction to Python
Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. As part of our free Introduction to Python Course, you will learn the fundamentals of Python. It's possible to use Python without any additions, but there are quite a few open-source libraries that make Python data tasks much easier. We will show some popular and useful Python libraries for data scientists and engineers. We will cover Pandas, Numpy, Matplotlib and Seaborn packages.
Introduction to Python Course
Unit 1: Python Fundamentals
Python Fundamentals will cover Python Lists, Python Tuples, Python Dictionary, type conversion, Python operators, Python If Else, Python Loops, Arguments, Parameters and Lambda. We will also cover how to set up your environment for Python.
Unit 2: Numpy - Python for Data Analysis
Numpy is the core library for scientific computing in Python. It provides a high-performance multidimensional array object and tools for working with these arrays.
Unit 3: Pandas - Python for Data Analysis
Pandas is an open-source Python package that provides high-performance, easy-to-use data structures and data analysis tools for the labelled data in Python programming language.
Unit 4: Matplotlib - Python for Data Visualisation
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
Unit 5: Seaborn - Python for Data Visualisation
Seaborn is the data visualization library based on Matplotlib that provides a high-level interface for drawing attractive and informative statistical graphics. Putting it simply, seaborn is an extension of Matplotlib with advanced features.
Unit 6: Bonus: Massive discount on our paid courses
When you subscribe for our paid course, we will give to a special discount on our paid courses.
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