Python Foundation

The Python Programming Course offers a comprehensive understanding of Python, a versatile and widely used language in software development. Suitable for beginners with no programming experience and experienced developers looking to expand their skills.

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Program Curriculum
Introduction to Python
  • Chapter 1: Introduction of Python Language and Coding Environment Setup - Learn about Python's basics and set up your coding environment.
  • Chapter 2: Variables in Python - Understand how variables work in Python and their importance in programming
  • Chapter 3: Data Types in Python - Explore the various data types available in Python, such as integers, floats, strings, and more
  • Chapter 4: Basic Functions in Python - Dive into essential functions in Python to perform common tasks efficiently
Work with Numpy
  • Chapter 5: Introduction of NumPy and Arrays - Get introduced to NumPy, a powerful library for numerical computing, and learn about arrays
  • Chapter 6: List, Tuples, set, and Dictionaries - Understand Python's built-in data structures and their applications.
  • Chapter 7: In-built Functions in Numpy - Explore the in-built functions provided by NumPy for array manipulation and mathematical operations.
  • Chapter 8: Program Implementation of Numpy - Apply your knowledge of NumPy to solve real-world problems through programming
Basics of Pandas
  • Chapter 9: Introduction of Pandas - Learn about Pandas, a data manipulation and analysis library, and its importance in data science.
  • Chapter 10: Series with Pandas - Dive into Pandas Series, a one-dimensional labeled array capable of holding data of any type.
  • Chapter 11: DataFrame with Pandas - Explore Pandas DataFrame, a two-dimensional labeled data structure with columns of potentially different types.
  • Chapter 12: Program Implementation of Pandas - Apply Pandas to analyze and manipulate data sets through practical programming exercises.
Basics of Matplotlib
  • Chapter 13: Introduction of Matplotlib - Get introduced to Matplotlib, a comprehensive library for creating static, animated, and interactive visualizations in Python.
  • Chapter 14: Different Type of Plots I - Learn about different types of plots such as line plots, scatter plots, and bar plots using Matplotlib.
  • Chapter 15: Different Type of Plots II - Further explore advanced plotting techniques and customization options with Matplotlib.
  • Chapter 16: Program Implementation of Matplotlib - Practice creating various types of plots and visualizations using Matplotlib in programming exercises.
Basics of Seaborn
  • Chapter 17: Introduction of Seaborn - Discover Seaborn, a Python visualization library based on Matplotlib, designed for statistical plotting.
  • Chapter 18: Different Type of Plots I - Explore Seaborn's capabilities in creating various statistical plots such as histograms, box plots, and violin plots.
  • Chapter 19: Different Type of Plots II - Learn more advanced techniques and visualizations with Seaborn for effective data representation.
  • Chapter 20: Program Implementation of Seaborn - Apply Seaborn to visualize and analyze data sets through practical programming tasks.

Batch 1Live Online Class

Weekday (Mon - Fri)

15th July - 9th August

Batch 2Live Online Class

Weekday (Mon - Fri)

15th July - 9th August

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Assignments for Every chaptercheckcheck
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  • No programming experience needed - We will teach you everything you need to know

  • A Mac or Windows PC computer with access to the internet

  • No paid software required – we will use Favo’s shared resources which will give you the exposure to understand Jupyter notebook and google colab

  • Our trainers will walk you through, step-by-step how to get all the software installed, set up and libraries

Skills you will learn:

  • Master Python basics for coding and computational logic

  • Utilize NumPy for advanced numerical operations

  • Learn essential data structures in Python

  • Analyze data effectively with Pandas

  • Visualize data using Matplotlib's diverse plotting options

  • Create aesthetically pleasing visualizations with Seaborn's statistical capabilities


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