Python for Data Science

Categories: Data Science
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About Course

Course Description:

Unleash the power of Python in the realm of data science. This comprehensive course is designed to equip you with the essential skills and knowledge needed to excel in the data-driven world. Python, a versatile and widely used programming language, will be your tool of choice as you delve into data analysis, visualization, and machine learning.

Course Highlights:

  1. Python Fundamentals: Master the basics of Python programming, including data structures, functions, and control flow.
  2. Data Manipulation: Learn how to efficiently manipulate and analyze data using libraries like Pandas and NumPy.
  3. Data Visualization: Create captivating data visualizations with Matplotlib and Seaborn to make insights accessible.
  4. Machine Learning: Explore the foundations of machine learning, including supervised and unsupervised learning algorithms.
  5. Real-world Applications: Apply your Python skills to practical data science projects and scenarios.
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What Will You Learn?

  • Data preprocessing and cleaning.
  • Statistical analysis and hypothesis testing.
  • Machine learning model development and evaluation.
  • Data-driven decision-making and problem-solving.

Course Content

1: Introduction to Python
Lessons: What is Python? Setting Up Python Your First Python Program Python’s Syntax and Structure Learning Objectives: By the end of this module, students will understand what Python is, how to set it up, write and run their first Python program, and grasp Python’s syntax and structure. Real-World Applications: Apply Python for simple script-based tasks and grasp the basics. Activities: Write a Python program to print a message Experiment with Python’s interactive mode

2: Variables and Data Types
Lessons: Variables and Assignments Numeric Data Types Strings and Text Data Working with Lists and Dictionaries Learning Objectives: After this module, students will be able to declare variables, work with numeric and text data, and understand Python’s data structures. Real-World Applications: Use Python to store and manipulate data effectively. Activities: Declare and use variables for practical applications Create and manipulate lists and dictionaries

3: Control Structures and Functions
Lessons: Conditional Statements Loops and Iterations Writing Functions Using Built-in Functions Learning Objectives: By the end of this module, students will understand how to create conditional statements, loops, and functions in Python, making their code more dynamic and functional. Real-World Applications: Use control structures and functions to automate tasks and make decisions in your programs. Activities: Write a program using conditional statements Create and use functions in Python

4: Python Modules and Libraries
Lessons: Understanding Modules and Libraries Importing and Using Modules Popular Python Libraries Exploring the Python Standard Library Learning Objectives: After this module, students will be familiar with Python modules, libraries, and how to use them to expand their coding capabilities. Real-World Applications: Leverage Python libraries to solve real-world problems efficiently. Activities: Import and use external modules in Python programs Explore and utilize the Python Standard Library

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