Python Programming: Data Analysis & Computer Science

[Updated 2024 (CPD QS)]

Join 'Python Programming: Data Analysis & Computer Science' and follow the journey of a data analyst who revolutionized her career with Python. From basics to complex data structures, this course is your pathway to unlocking the power of Python in the digital world. Transform data into insights and action.

'Python Programming: Data Analysis & Computer Science' is a comprehensive course designed to take you from Python novice to proficient programmer. Discover the essentials of Python, including data types, operators, and structures. Learn about control flow, functions, arrays, iterators, and file manipulation.

This course is perfect for those seeking to delve into the realms of data analysis and computer science using Python. Each module is crafted to build your skills step by step, ensuring a solid foundation. Ready to embark on a journey of coding excellence?

Enrol now and start your transformation into a Python programming pro!

Learning Outcomes:

After completing this course, you will be able to:

• Write efficient Python code using various data types and structures.
• Develop and implement functions and control flow to solve complex problems.
• Utilize arrays, iterators, and generators for data processing.
• Perform file manipulation for data analysis.
• Apply Python programming skills in real-world data analysis scenarios.

Reed Courses Certificate of Completion

Digital certificate - Included

Hardcopy Certificate of Completion

Hard copy certificate - £9.99

• Course Introduction 01:10

  • 1: Course Instructor Introduction Preview 01:10

• Module 01: Getting Started with Python 1:01:30

  • 2: 001 Why Learn Coding 04:32
  • 3: 002 Why Learn Python 03:47
  • 4: 003 Gearing up Linux Machine For Python Programming 14:41
  • 5: 004 Gearing Up Windows For Python 13:23
  • 6: 005 Integrate Python and Git Bash with vscode 03:02
  • 7: 006 Gearing Up the MacOS for Python Programming 05:31
  • 8: 007 Installing Jupyter Notebook in Windows 06:00
  • 9: 008 Hello World in Jupyter notebook 10:34

• Module 02: Data Types and Operators 1:54:15

  • 10: 001 Arithmetic Operators 13:41
  • 11: 002 order of evaluation 08:55
  • 12: 003 Variable and Assignment Operators 12:11
  • 13: 004 Correct Variable Names 08:15
  • 14: 005 Integer, Float and Complex Numbers in Python 10:33
  • 15: 006 Boolean, Comparison Operator and Logical Operator 20:23
  • 16: 007 Strings in python 06:41
  • 17: 008 type and type casting 10:20
  • 18: 009 String Methods in Python 09:00
  • 19: 010 Taking Input from User 04:53
  • 20: 011 Exercise 09:23

• Module 03: Data Structures 1:58:47

  • 21: 1. Lists in python 15:42
  • 22: 2. Necessitites in List 13:52
  • 23: 3. List Methods 19:22
  • 24: 4. Tuples in Python 13:50
  • 25: 5. Sets in Python 14:08
  • 26: 6. Dictionary, Mutable, Accessing Items 08:07
  • 27: 7 Dublicates, Constructor and data Types in Dictionary 05:56
  • 28: 8 Access and add items in Dictionaries 05:45
  • 29: 9 Nested Dictionaries and Dictionary Methods 10:16
  • 30: 10 Exercise 11:49

• Module 04: Control Flow 1:15:26

  • 31: 00 Introduction 01:10
  • 32: 01 conditional statements 10:21
  • 33: 02 short hand if else 10:51
  • 34: 03 Nested if 04:39
  • 35: 04 for loops 13:20
  • 36: 05 While Loops in Python 07:14
  • 37: 06 while vs for loop 06:55
  • 38: 07 Break Continue Statment 06:30
  • 39: 08 Try and Except 06:57
  • 40: 09 Exercise 07:29

• Module 05: Functions 48:58

  • 41: Lec 01 Intro to Functions 04:42
  • 42: Lec 02 Arguments, parameters and multiple arguments 09:20
  • 43: Lec 03 Arbitrary arguments, keyword arguments, arbitrary keyword arguments 09:42
  • 44: Lec 04 Default parameter value and Passing a list as parameters 09:19
  • 45: Lec 05 Return values and Pass statements 06:28
  • 46: Lec 06 Exercise 09:27

• Module 06: Python Arrays, Iterators and Generators 49:20

  • 47: Lec 01 Array, Length of Array, Accessing Elements of Array 09:47
  • 48: Lec 02 Adding, Removing Elements in Array, Array Methods 12:17
  • 49: Lec 03 Iterator in Python 13:44
  • 50: Lec 04 Generators in Python 06:34
  • 51: Lec 05 Exercise 06:58

• Module 07: File Manipulation 27:46

  • 52: 001 File Hancdling and Syntax 05:12
  • 53: 002 Reading the File, Line Extraction and Parsing 11:01
  • 54: 003 Appending and Writing the Files in Python 06:28
  • 55: 004 Create and Delete a File 05:05

This course offers an immersive experience into Python programming, focusing on data analysis and computer science applications. You will gain hands-on experience in writing Python code, tackling real-world problems, and processing data efficiently. The course is structured to provide a progressive learning curve, from understanding the basics of Python programming to exploring advanced data structures and file manipulation techniques. It's an ideal blend of theoretical knowledge and practical application, making it suitable for those aiming to enhance their coding skills in the evolving landscape of data analysis and computer science.

*** PYTHON FOR DATA ANALYSIS: BECOME A PRO PYTHON PROGRAMMER TODAY ***

Module 01: Getting Started with Python

• Why Learn to Code?
• Why Python?
• Installing Python on Windows
• Installing Python on MAC
• Installing python on Linux
• Get your Integrated Development Environment
• Run Your First Code, “Hello World”

Module 02: Data Types and Operators in Python

• Arithmetic Operators
• Variables and Assignment Operators
• Numeric Operators
• Order of Evaluation
• Correct Variable names
• Integers and Floats
• Booleans, Comparison Operators, and Logical Operators
• Strings in Python
• Type and Type Conversion
• String Methods
• Taking inputs
• Exercise

Module 03: Data Structures for Python

• Lists and Membership Operators
• Necessity of Lists
• List Methods
• Tuples
• Sets
• Dictionaries
• Exercise

Module 04: Control Flow in Python

• Conditional Statements
• Boolean Expressions for Conditions
• For Loops
• While Loops
• For Loop vs While Loops
• Try and Except Structure
• Break, Continue
• Exercise

Module 05: Functions in Python

• Defining Function
• Passing Arguments
• Returning values
• Documentation
• Exercise

Module 06: Python Arrays, Iterators and Generators

• What is an Array?
• Access the Elements of an Array
• The Length of an Array
• Looping Array Elements
• Adding Array Elements
• Removing Array Elements
• Array Methods
• Iterators and Generators
• Generator Expression
• Exercise

Module 07: File Manipulation in Python

• Opening the Files
• Writing, Reading, Creating and Deleting the Files
• Extracting lines from files in Python (Parsing and Extraction)
• Important Python File methods

• Beginners in programming aspiring to learn Python.
• Data analysts seeking to enhance their coding skills.
• Computer science students and enthusiasts.
• Professionals in various fields aiming to integrate Python into their work.
• Educators and trainers in computer science and data analysis.

All you need is a smart device, a reliable internet connection, and a basic command of English and you're good to go!

• Python Developer (£30,000 - £60,000)
• Data Analyst (£25,000 - £50,000)
• Software Engineer (£35,000 - £70,000)
• Data Scientist (£40,000 - £80,000)
• Machine Learning Engineer (£45,000 - £85,000)

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