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Python Programming for Beginners

Self-paced videos, Lifetime access, Study material, Certification prep, Technical support, Course Completion Certificate

Uplatz

Summary

Price
£19 inc VAT
Study method
Online, On Demand What's this?
Duration
30.8 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Certificate of completion - Free
  • Reed courses certificate of completion - Free
8 students purchased this course

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Overview

Uplatz offers this comprehensive course on Python. It is a self-paced course with video tutorials. You will be awarded Course Completion Certificate by Uplatz at the end of the course.

Python is emerging as one of the most preferred languages in data science and data analysis as more and more data scientists choose open source scripting languages ??for machine learning and their working algorithms. in data science. The reason for this growing popularity over the years is due to Python's easy-to-code syntax and large number of built-in libraries and frameworks.

Python, a very simple programming language that has encouraged many programmers to pursue careers in Python outside of other languages.

Advanced Python methods

  • Data collection
  • Data processing and storage
  • BONUS tips and methods!

If you're looking for a course that will take you from beginner to expert, go no further! With our courses, we can ensure that the knowledge you learn will help you in your career.

With Uplatz Python Programming (Advanced) Course you will learn-

  • Learn many advanced Python methods and variables.
  • Learn how to scan, process and store data.
  • Learn how to create your own methods and functions.
  • Take a huge step towards OOP, Object Orientated Programming.

Certificates

Certificate of completion

Digital certificate - Included

Course Completion Certificate by Uplatz

Reed courses certificate of completion

Digital certificate - Included

Will be downloadable when all lectures have been completed

Curriculum

1
section
88
lectures
30h 47m
total

    • 1: 1 - INTRODUCTION TO PYTHON 10:21
    • 2: 2 - BASIC ELEMENTS OF PYTHON 19:37
    • 3: 3 - INSTALLATION OF PYTHON 13:18
    • 4: 4 - INPUT AND OUTPUT STATEMENTS IN PYTHON 24:05
    • 5: 5 - DATA TYPES IN PYTHON 23:05
    • 6: 6.1 - OPERATORS IN PYTHON - PART 1 47:07
    • 7: 6.2 - OPERATORS IN PYTHON - PART 2 29:48
    • 8: 7 - TYPE CONVERSION IN PYTHON 23:39
    • 9: 8.1 - BASIC PROGRAMMING IN PYTHON - PART 1 15:57
    • 10: 8.2 - BASIC PROGRAMMING IN PYTHON - PART 2 05:14
    • 11: 9 - MATH MODULE IN PYTHON 26:44
    • 12: 10.1 - CONDITIONAL STATEMENTS IN PYTHON - PART 1 28:24
    • 13: 10.2 - CONDITIONAL STATEMENTS IN PYTHON - PART 2 19:27
    • 14: 10.3 - CONDITIONAL STATEMENTS IN PYTHON - PART 3 13:40
    • 15: 10.4 - NESTED IF ELSE STATEMENTS 11:05
    • 16: 11.1 - LOOPING IN PYTHON 25:07
    • 17: 11.2 - BREAK AND CONTINUE KEYWORDS IN PYTHON 20:49
    • 18: 11.3 - PRIME NUMBER PROGRAM IN PYTHON 17:31
    • 19: 11.4 - WHILE LOOP IN PYTHON 35:35
    • 20: 11.5 - NESTED FOR LOOP IN PYTHON - PART 1 12:34
    • 21: 11.6 - NESTED FOR LOOP IN PYTHON - PART 2 12:49
    • 22: 12.1 - FUNCTIONS IN PYTHON 19:28
    • 23: 12.2 - PASSING ARGUMENTS TO FUNCTIONS 09:00
    • 24: 12.3 - RETURN KEYWORD IN PYTHON 12:16
    • 25: 12.4 - CALLING A FUNCTION - PART 1 15:08
    • 26: 12.5 - CALLING A FUNCTION - PART 2 20:17
    • 27: 12.6 - CALLING A FUNCTION - PART 3 19:27
    • 28: 12.7 - FUNCTIONS - ARBITRARY ARGUMENTS 10:34
    • 29: 12.8 - FUNCTIONS - KEYWORD ARGUMENTS 06:56
    • 30: 12.9 - FUNCTIONS - DEFAULT ARGUMENTS 06:58
    • 31: 12.10 - GLOBAL AND LOCAL VARIABLES 19:37
    • 32: 12.11 - GLOBAL AND LOCAL KEYWORDS 10:44
    • 33: 13.1 - STRINGS IN PYTHON 17:43
    • 34: 13.2 - STRING METHODS IN PYTHON 21:53
    • 35: 13.3 - STRING FUNCTIONS IN PYTHON 28:02
    • 36: 13.4 - STRING INDEXING IN PYTHON 13:52
    • 37: 14.1 - INTRODUCTION TO LISTS 06:31
    • 38: 14.2 - BASICS OF LISTS IN PYTHON 33:09
    • 39: 14.3 - LIST METHODS 32:44
    • 40: 14.4 - LINEAR SEARCH ON LIST 23:20
    • 41: 14.5 - BIGGEST AND SMALLEST NUMBER IN THE LIST 14:40
    • 42: 14.6 - DIFFERENCE BETWEEN 2 LISTS 13:22
    • 43: 15 - TUPLES IN PYTHON 20:19
    • 44: 16.1 - INTRODUCTION TO SETS IN PYTHON 32:43
    • 45: 16.2 - SET OPERATIONS 26:56
    • 46: 16.3 - SET EXAMPLES 11:05
    • 47: 17.1 - INTRODUCTION TO DICTIONARIES 14:47
    • 48: 17.2 - CREATING AND UPDATING DICTIONARIES 32:50
    • 49: 17.3 - DELETING ITEMS IN DICTIONARY 08:07
    • 50: 17.4 - VALUES AND ITEMS IN DICTIONARY 13:14
    • 51: 17.5 - DICTIONARY METHODS 18:47
    • 52: 18 - BUILT-IN METHODS IN PYTHON 20:25
    • 53: 19 - LAMBDA FUNCTION 15:29
    • 54: 20.1 - FILE HANDLING IN PYTHON - PART 1 15:58
    • 55: 20.2 - FILE HANDLING IN PYTHON - PART 2 36:13
    • 56: 21.1 - EXCEPTION HANDLING IN PYTHON 08:46
    • 57: 21.2 - EXCEPTION HANDLING IN PYTHON EXAMPLES 25:04
    • 58: 22.1 - PYTHON PROGRAMS - PART 1 18:41
    • 59: 22.2 - PYTHON PROGRAMS - PART 2 10:47
    • 60: 22.3 - PYTHON PROGRAMS - PART 3 21:39
    • 61: 22.4 - PYTHON PROGRAMS - PART 4 14:08
    • 62: 22.5 - BUBBLE SORT 35:37
    • 63: 23.1 - OPERATOR PRECEDENCE IN PYTHON - PART 1 14:51
    • 64: 23.2 - OPERATOR PRECEDENCE IN PYTHON - PART 2 11:29
    • 65: 24 - RECURSION IN PYTHON 22:16
    • 66: 25.1 - BINARY SEARCH IN PYTHON - PART 1 23:19
    • 67: 25.2 - BINARY SEARCH IN PYTHON - PART 2 35:05
    • 68: 26.1 - OBJECT-ORIENTED PROGRAMMING IN PYTHON - PART 1 21:53
    • 69: 26.2 - OBJECT-ORIENTED PROGRAMMING IN PYTHON - PART 2 17:42
    • 70: 26.3 - DIFFERENCE BETWEEN OOPS AND PROCEDURAL PROGRAMMING 06:36
    • 71: 26.4 - OOPS PROGRAMS IN PYTHON - PART 1 27:51
    • 72: 26.5 - OOPS PROGRAMS IN PYTHON - PART 2 37:24
    • 73: 26.6 - OBJECT CREATION IN PYTHON 24:10
    • 74: 26.7 - OOPS TERMINOLOGY AND FUNCTIONS 24:41
    • 75: 26.8 - BUILT IN CLASS ATTRIBUTES AND GARBAGE COLLECTION 27:26
    • 76: 26.9 - INHERITANCE IN PYTHON - PART 1 19:02
    • 77: 26.10 - INHERITANCE IN PYTHON - PART 2 29:26
    • 78: 26.11 - INHERITANCE IN PYTHON - PART 3 31:44
    • 79: 26.12 - POLYMORPHISM IN PYTHON - PART 1 24:47
    • 80: 26.13 - POLYMORPHISM IN PYTHON - PART 2 14:02
    • 81: 27.1 - TIME MODULE IN PYTHON - PART 1 36:23
    • 82: 27.2 - TIME MODULE IN PYTHON - PART 2 44:51
    • 83: 27.3 - CALENDAR MODULE IN PYTHON 32:04
    • 84: 27.4 - CALENDAR METHODS IN PYTHON 37:03
    • 85: 28.1 - BOOLEAN IN PYTHON 09:32
    • 86: 28.2 - PYTHON ITERATORS 09:30
    • 87: 29.1 - PYTHON PROGRAMS AND SUMMARY - PART 1 46:37
    • 88: 29.2 - PYTHON PROGRAMS AND SUMMARY - PART 2 23:28

Course media

Description

Python Programming - Course Syllabus

(A) Basics of Python

  • Python Indentation
  • Comments and Quotation
  • Python Identifiers and Keywords
  • Variables
  • Reading data from user
  • Working with input function
  • Python data types
  • Type conversion and eval

(B) Introduction to Data Structure

  • String Data Structure
  • List Data Structure
  • Tuple Data Structure
  • Set Data Structure
  • Dictionary Data Structure

(C) Functions and Arguments

(D) Lambda Function

(E) Looping

(F) Advance Concepts in Data Structure

  • List Comprehension
  • Dictionary Comprehension
  • Nested Data Structure

(G) File Handling

(H) OOPS Concept

(I) Modules

(J) Exception Handling

Who is this course for?

  • Beginners with no prior programming experience who want to learn Python from scratch
  • Students studying computer science, engineering, or related technical fields
  • Professionals looking to start a career in software development or IT
  • Non-programmers (e.g., from finance, business, science) transitioning into tech or automation
  • Self-learners interested in understanding the fundamentals of programming
  • Developers from other languages (like Java, C++, or PHP) wanting to learn Python
  • Data science or AI/ML aspirants needing a strong foundation in Python programming
  • Analysts and researchers who want to automate tasks or handle data using Python
  • Web developers preparing to use Python for backend development (e.g., Django, Flask)
  • QA testers and automation engineers learning Python for scripting and testing tools
  • Engineers and hobbyists working on hardware or IoT projects using Python
  • Professionals involved in scripting, file handling, and task automation
  • Educators and trainers designing beginner-level Python courses or coding workshops
  • Students preparing for coding interviews or competitive programming using Python
  • Bootcamp participants and online learners enrolled in Python-based curriculum
  • Career changers looking to enter tech roles with Python as their first language
  • Developers who want to improve their coding structure using functions, OOP, and modules
  • Anyone seeking to understand modern Python features like comprehensions and exception handling

Requirements

Passion and determination to achieve your goals!

Career path

  • Python Developer
  • Software Engineer
  • Cloud Engineer
  • Software Developer
  • Backend Developer
  • Web Developer
  • Automation Engineer
  • QA Engineer (Python Scripting)
  • Data Analyst
  • Junior Data Scientist
  • Machine Learning Engineer
  • AI Developer
  • Scripting Developer
  • DevOps Engineer
  • Game Developer
  • IoT Developer
  • Research Assistant
  • Application Support Engineer
  • Technical Support Engineer
  • Full Stack Developer

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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.

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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.
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