Python Programming from Basics to Advanced

BY
Udemy

Begin your coding journey by learning both basic as well as advanced concepts ad techniques associated with Python programming.

Mode

Online

Fees

₹ 2699

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

The Python Programming from Basics to Advanced certification course was established by Rahul Tiwari - Professional Data Scientist & Trainer and is offered on Udemy to help students gain the basic skills and knowledge in Python programming to help them land high-paying developer roles. The Python Programming from Basics to Advanced online course by Udemy focuses on teaching Python in a hands-on approach, with each session accompanied by a full code video and a programming journal.

Python Programming from Basics to Advanced online classes begin with basic Python concepts such as strings, operators, functions, and flow control before moving on to more advanced topics such as object-oriented programming, exception handling, database integration, and regular expressions. This course covers not only Python but also data science principles such as feature scaling, encoding, missing value treatment, and outlier treatment, as well as Python-based data science tools such as Pandas, Numpy, Seaborn, and Matplotlib.

The highlights

  • Certificate of completion
  • Self-paced course
  • 62 hours of pre-recorded video content
  • 2 articles
  • 15 downloadable resources

Program offerings

  • Certificate
  • Online course
  • Quizzes
  • 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 2,699
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Data science knowledge

After completing the Python Programming from Basics to Advanced online certification, students will be introduced to the basic concepts of Python programming such as strings, functions, operators, and flow control. Students will learn about Dfply, Pandas, Numpy, Seaborn, and Matplotlib, which are all data science technologies that are supported by Python programming. Students will study object-oriented programming, regular expressions, exceptional handling, and database connecting techniques and approaches. Students will also become skilled at various data science concepts like missing value treatment, outlier treatment, encoding, and feature scaling.

The syllabus

Slack Details

  • Slack Details for Communication

Live Sessions

  • Live Session 0 - 06072021 - Data Analysis using Python - Video Games
  • Live Session 1 - 08072021 - Basic Programming & Bug Fixing in Python

Python Installation and Introduction

  • How this course helped a fresher
  • About Instructor and the Feedback
  • Python history and features

Python Data Types

  • Python Data Types - Part 1
  • Python Data Types - Part 2

Python Collection Data Types

  • Lists
  • Tuples, Dictionaries and Sets

Operators in Python

  • Various operators in Python
  • Operators in Python - Part 2

Input and Output in Python

  • Input Ways in Python
  • Output ways in Python

Flow Control in Python

  • if - else statements and for loops in python
  • while loops in Python

String Operations in Python

  • String Operations
  • String Operation - Examples

Functions in Python

  • Functions in Python - Part 1
  • Functions in Python - Part 2
  • Functions in Python - Part 3
  • Functions in Python - Part 4
  • Functions in Python - Part 5
  • Functions in Python - Part 6

Exception Handling in Python

  • Exception Handling in Python - Part1
  • Exception Handling in Python - Part2
  • Exception Handling in Python - Part3
  • Exception Handling - Example
  • Exception Handling - Custom Message

File Handling in Python

  • File Handling in Python - Part 1
  • File Handling in Python - Part 2

OOPs Concept in Python

  • OOPs 1 - An Introduction
  • OOPs 2
  • OOPs 3
  • OOPs 4
  • OOPs 5
  • OOPs 6
  • OOPs 7
  • OOPs 8
  • OOPs 9
  • OOPs 10
  • OOPs 11
  • OOPs 12
  • OOPs 13

Multithreading in Python

  • Multi Threading - Part 1
  • Multi Threading - Part 2
  • Multi Threading - Part 3
  • Multi Threading - Part 4
  • Multi Threading - Part 5

Regular Expression in Python

  • Regular Expression in Python - Part 1
  • Regular Expression in Python - Part 2

Numpy Package in Python

  • Numpy - Part 1
  • Numpy - Part 2
  • Numpy - Part 3

Pandas Package in Python

  • Pandas - Part 1
  • Pandas - Part 2
  • Pandas - Part 3
  • Pandas - Part 4
  • Pandas - Part 5

dfply - An understanding

  • dfply - An understanding

Data Visualization in Python using Matplotlib and Seaborn

  • Matplotlib - Visualization
  • Seaborn - Visualization

Data Preprocessing in Python

  • Data Preprocessing - Missing Value Treatment
  • Data Preprocessing - Outlier Treatment
  • Data Preprocessing - Feature Scaling - Part1
  • Data Preprocessing - Feature Scaling(Handson) - Part 2

Python Connection with Oracle

  • Python Connection with Oracle - Part 1 (Inserts)
  • Python Connection with Oracle - Part 2 (Other DMLs)

Exploratory Data Analysis

  • Exploratory Data Analysis - Part 1
  • Exploratory Data Analysis - Part 2

Extra Problems and Solutions

  • Extra Problems and Solutions - Part 1
  • Extra Problems and Solutions - Part 2
  • Extra Problems and Solutions - Part 3

Python Quizzes and Practice Problems

  • Python Quizzes
  • Python Introduction - Question 1 - If and else
  • Python Introduction - Question 2 - Arithmetic Operators
  • 01. Calculate the average of numbers in a given list
  • 02. Exchange the Values of Two Numbers Without Using a Temporary Variable
  • 03. Read a Number n and Compute n+nn+nnn
  • 04. Compute Simple Interest
  • 05. Read Height in Centimeters and then Convert the Height to Feet and Inches

Instructors

Mr Rahul Tiwari

Mr Rahul Tiwari
Instructor
Freelancer

Articles

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