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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 ...Read more
Online
₹ 2699
Quick Facts
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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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
Who it is for
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
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
Instructor
Freelancer
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