Skip to content
Play overlay
Preview this course

Python: From Data Types to Numpy, Pandas & Career - CPD Certified

Learn Programming in Python | CPD Accredited Provider | Easy Refund Policy | Lifetime Access

Learndrive

Summary

Price
£12 inc VAT
Study method
Online, On Demand What's this?
Duration
15.7 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed courses certificate of completion - Free
Additional info
  • Tutor is available to students
2 students purchased this course

Add to basket or enquire

Overview

Embark on a journey of programming excellence with our comprehensive Python Programming course. From mastering the basics to diving deep into Python scripting and libraries, we've designed this course to make you a proficient Python developer. Explore the world of data with NumPy and Pandas, and unlock exciting career opportunities in Python programming. Start your coding adventure today with our Python course.

Learning Outcomes of this Python Programming Course:

  • Apply fundamental Python programming concepts.
  • Utilize Python basic data types like strings, numbers, and lists.
  • Manage data structures using Python operators.
  • Employ advanced Python data types such as dictionaries and sets.
  • Create logical algorithms with "Python Control Flow" concepts.
  • Develop reusable code with Python functions.
  • Implement error handling and user input in Python.
  • Use advanced Python functions, including lambda and decorators.
  • Leverage Python libraries for scripting and data analysis.
  • Analyze data efficiently with NumPy and Pandas in Python.

Curriculum

16
sections
130
lectures
15h 42m
total

    • 1: Python: 1.1. Intro To Python Programming 05:20
    • 2: Python: 1.2 What is Python Programming 09:30
    • 3: Python: 1.3 Who is This Course For 04:33
    • 4: Python: 1.4 Python Marketplace 05:46
    • 5: Python: 1.5 Python Job Opportunities 04:43
    • 6: Python: 1.6 Getting a python job w.o degree 08:20
    • 7: Python: 1.7 Python Job Roles 08:41
    • 8: Python: 1.8 Python Course Structure 04:18
    • 9: Python: Section 1 MCQ 01:00

    • 10: Python: 2.1. Getting Familiar With Python (section overview) 05:56
    • 11: Python: 2.2 Installing Python on Windows 09:36
    • 12: Python: 2.3 Anaconda and Jupyter Notebooks Part1 07:30
    • 13: Python: 2.4 Anaconda and Jupyter Notebooks Part2 16:24
    • 14: Python: 2.5 Python Syntax 02:13
    • 15: Python: 2.6 Line Structure Part1 02:43
    • 16: Python: 2.7. Line Structure Part2 07:11
    • 17: Python: 2.8 Comments 05:01
    • 18: Python: 2.9 Joining Lines 05:00
    • 19: Python: 2.10 Multiple Statements on a Single Line 04:52
    • 20: Python: 2.11 Indentation 07:39
    • 21: Python: Section 2 MCQ 01:00

    • 22: Python: 3.1. Python Basic Data Types (section overview) Preview 08:25
    • 23: Python: 3.2 Python Variables 08:09
    • 24: Python: 3.3 Integers and Float 08:26
    • 25: Python: 3.4 Strings Overview 09:50
    • 26: Python: 3.5 String Manipulation 07:17
    • 27: Python: 3.6 String Indexing 04:28
    • 28: Python: 3.7 String Slicing 08:16
    • 29: Python: 3.8 Booleans 04:53
    • 30: Python: 3.9 Printing 09:48
    • 31: Python: 3.10 Mini-Project 1 - Letter Counter (1) 19:55
    • 32: Python: Section 3 MCQ 01:00
    • 33: Care for a Feedback? 01:00 PDF

    • 34: Python: 4.1. Python Operators (section overview) 04:11
    • 35: Python: 4.2 Arithmetic Operators 08:17
    • 36: Python: 4.3 Assignment Operators 03:40
    • 37: Python: 4.4 Comparison Operators 09:20
    • 38: Python: 4.5 Logical Operators 12:36
    • 39: Python: 4.6 Identity Operators (Need slide update as (Equality is misspelled) 04:41
    • 40: Python: 4.7 Membership Operators 02:01
    • 41: Python: 4.8 Bitwise Operators 07:49
    • 42: Python: Section 4 MCQ 01:00

    • 43: Python: 5.1. Python Advanced Data Types (section overview) Preview 10:37
    • 44: Python: 5.2 List Overview 04:38
    • 45: Python: 5.3 List Indexing and Slicing 04:25
    • 46: Python: 5.4 Tuples 02:20
    • 47: Python: 5.5 Sets 06:01
    • 48: Python: 5.6 Dictionary 10:40
    • 49: Python: 5.7 When to use each one 04:31
    • 50: Python: 5.8 Compound Data Types 02:43
    • 51: Python: Section 5 MCQ 01:00

    • 52: Python: 6.1 Control Flow Part 1 (section overview) 15:00
    • 53: Python: 6.2 Basic Conditional Statements 13:38
    • 54: Python: 6.2 Intro to Control Flow 00:56
    • 55: Python: 6.3 More Conditional Statements 05:04
    • 56: Python: 6.4 For Loops 09:50
    • 57: Python: 6.5 While Loops 11:46
    • 58: Python: Section 6 MCQ 01:00

    • 59: Python: 7.0 Control Flow Part 2 (section overview) 02:28
    • 60: Python: 7.1 Break Statements 07:59
    • 61: Python: 7.2 Continue Statements 04:51
    • 62: Python: 7.3 Zip Function 07:20
    • 63: Python: 7.4 Enumerate Function 03:58
    • 64: Python: 7.5 List Comprehension 04:27

    • 65: Python: 8.0 Python Functions (section overview) 02:49
    • 66: Python: 8.1 Intro to Functions 02:16
    • 67: Python: 8.2 Python Help Function 03:11
    • 68: Python: 8.3 Defining Functions 09:29
    • 69: Python: 8.4 Variable Scope 08:12
    • 70: Python: 8.5 DocStrings 03:44

    • 71: Python: 9.0 Error Handling and User Input (section overview) 01:48
    • 72: Python: 9.1 Intro to Error Handling 02:48
    • 73: Python: 9.2 User Input 04:21
    • 74: Python: 9.3 Syntax Errors 04:00
    • 75: Python: 9.4 Exceptions 11:22
    • 76: Python: 9.5 Handling Exceptions 1 08:29
    • 77: Python: 9.6 Handling Exceptions 2 08:17

    • 78: Python: 10.0 Python Advanced Functions (section overview) 05:10
    • 79: Python: 10.1 Lambda Functions 05:29
    • 80: Python: 10.2 Functions args and kwargs 10:01
    • 81: Python: 10.3 Iterators 08:12
    • 82: Python: 10.4 Generators and Yield 11:53
    • 83: Python: 10.5 Map Functions 14:24
    • 84: Python: 10.6 Filter 08:03
    • 85: Python: Section 10 MCQ 01:00

    • 86: Python: 11.0 Scripting and Libraries (section overview) 04:29
    • 87: Python: 11.1 What is a script. 01:24
    • 88: Python: 11.2 What is an IDE 17:20
    • 89: Python: 11.3 What is a text editor 11:46
    • 90: Python: 11.4 from jupyter notebook to vscode 1 14:45
    • 91: Python: 11.5 from jupyter notebook to vscode 2 05:03
    • 92: Python: 11.6 Importing Scripts 03:04
    • 93: Python: 11.7 Standard Libraries 04:13
    • 94: Python: 11.8 Third Party Libraries 05:35
    • 95: Python: Section 11 MCQ 01:00

    • 96: Python: 12.0 Numpy section overview 04:07
    • 97: Python: 12.1 What is NumPy 04:28
    • 98: Python: 12.2 Why NumPy 04:09
    • 99: Python: 12.3 NumPy Arrays 10:23
    • 100: Python: 12.4 Reshaping, Modifying and Accessing NumPy arrays 07:19
    • 101: Python: 12.5 Slicing and Copying 05:52
    • 102: Python: 12.6 Inserting , Deleting, Appending 09:45
    • 103: Python: 12.7 Logical Indexing 03:43
    • 104: Python: 12.8 Broadcasting 08:20

    • 105: Python: 13.1 Pandas 16:43
    • 106: Python: 13.2 Pandas Series 16:58
    • 107: Python: 13.3 Pandas Series Manipulation 16:32
    • 108: Python: 13.4 Pandas DataFrame 17:04
    • 109: Python: 13.5 Pandas DataFrame Manipulation 12:54
    • 110: Python: 13.6 Dealing with Missing Values 10:09

    • 111: Python: 14.1 Functional vs OOP 06:16
    • 112: Python: 14.2 OOP key defintions 04:04
    • 113: Python: 14.3 Create your First Class 12:09
    • 114: Python: 14.4 How to create and use Objects 06:04
    • 115: Python: 14.5 Modifying Attributes 12:28

    • 116: Python: 15.1 Python Decorators 27:09
    • 117: Python: 15.2 Property Decorator 08:43
    • 118: Python: 15.3 Class Methods Decorator 07:11
    • 119: Python: 15.4 Static Methods Decorators 10:28
    • 120: Python: 15.5 Inheritance 20:36
    • 121: Python: Section 15 MCQ 01:00

    • 122: Python: 16.1. Starting a Career in Python Overview 05:55
    • 123: Python: 16.2. Getting Started with Freelancing 09:26
    • 124: Python: 16.3. Building a Brand 11:56
    • 125: Python: 16.4. Personal Branding 13:08
    • 126: Python: 16.5. Importance of Website Blog 04:22
    • 127: Python: 16.6. Networking Do_s Don_ts 05:31
    • 128: Python: 16.7. Top Freelance Sites 08:04
    • 129: Python: 16.8. Creating a Python Developer Resume 06:00
    • 130: Thank You ! 01:00 PDF

Course media

Description

Explore the captivating world of Python programming with our comprehensive Python course. Whether you're a novice eager to grasp the fundamentals or an aspiring data analyst aiming to master Python libraries like NumPy and Pandas, our course is tailored to your Python learning journey. Don't miss this chance to boost your career prospects and embark on a fulfilling path in the realm of Python programming today!

Who is this course for?

This Course is suitable for anyone interested to further progress there career in:

  • Level 1 Award in Introduction to Python Programming
  • Level 2 Award in Python Programming
  • Level 3 Award in Python Programming
  • Level 2 Certificate in Python Programming
  • Level 3 Certificate in Python Programming
  • Level 2 Diploma in Python Programming
  • Level 3 Diploma in Python Programming
  • Level 4 Certificate in Python Programming
  • Level 4 Diploma in Python Programming
  • Level 5 Certificate in Python Programming
  • Level 5 Diploma in Python Programming
  • Level 6 Certificate in Python Programming
  • Level 6 Diploma in Python Programming
  • Level 7 Certificate in Python Programming
  • Level 7 Diploma in Python Programming
  • Level 8 Certificate in Python Programming
  • Level 8 Diploma in Python Programming

Requirements

This Python Program does not have any prerequisites or formal requirements.

Career path

Taking Python Program Course will open up a variety of career options for you.

  • Python Machine Learning Engineer
  • Python Data Scientist
  • Python Developer
  • Python Data Analyst
  • Software Engineer
  • Software Developer

Questions and answers

No questions or answers found containing ''.

SIMON asked:

will this course able me to create basic data sets in python to export into tensorart via .ckpt .pt .safetensors .ph file format kind regards Simon

Answer:

Yes, this Python Course covers various basic data types. Watch the course preview videos to learn more.

This was helpful. Thank you for your feedback.
Ask a question

Certificates

Reed courses certificate of completion

Digital certificate - Included

Will be downloadable when all lectures have been completed

Reviews

Currently there are no reviews for this course. Be the first to leave a review.

Leave a review

Legal information

This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
View all
Similar subjects: Python, Coding
Related searches: Online courses