
Explore the fundamentals of Python programming, including data storage and manipulation, lists, control structures, and user-defined functions, with hands-on exercises and practical assessments.
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Learn to work with lists in Python by creating and manipulating data in square brackets, storing heterogeneous values, and using indexing and slicing for access.
Explore practical list operations in Python, including creating lists, indexing, slicing, modifying, and deleting elements, and using functions like max, count, index, and round.
Learn Python control statements, including if-else with comparison operators, and the role of indentation; practice while and for loops, iterating over lists and ranges.
Learn to test conditions with if statements using equality and relational operators. Explore while and for loops to iterate ranges and lists, and understand indentation in Python.
Explore how to define and call functions in Python, pass parameters, return values, and modify logic using practical examples.
Explore the numpy package in Python, creating and manipulating arrays, performing slicing and indexing, and using numpy for mathematical computations in data science.
Python is a general purpose programming language. Now a days python is one of the best choice for machine learning application development. This course focuses on applications of python programming for data science applications.Companies worldwide are using Python to harvest insights from their data and gain a competitive edge.In our Introduction to Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses.In this course we we have provided theory as well as lab practice session. For executing the python programs we have used Google colab.
This course is divided into 5 chapters
Chapter 1: Introduction to Python Programming.
An introduction to the basic concepts of Python. Learn how to use Python interactively and by using a script. Create your first variables and acquaint yourself with Python's basic data types.
Chapter 2: Lists
Learn to store, access, and manipulate data in lists: the first step toward efficiently working with huge amounts of data.
Chapter 3: Control Statements
Learn use of if, for and while statements
Chapter 4: Functions
You'll learn how to use functions, methods, and packages to efficiently leverage the code that brilliant Python developers have written. The goal is to reduce the amount of code you need to solve challenging problems!
Chapter 5: Numpy NumPy is a fundamental Python package to efficiently practice data science. Learn to work with powerful tools in the NumPy array, and get started with data exploration.