Mastering Python- 01 -> 10 - Beginner to Advanced

Mastering Python: 0/1 -> 1/0 | Beginner to Advanced, available at $19.99, has an average rating of 4.6, with 70 lectures, based on 10 reviews, and has 550 subscribers.

You will learn about Learn about various Data Structures in Python Get introduced to Object Oriented Programming Learn writing functions from scratch Solving real-time use cases Handling Numpy Arrays Have an in-depth understanding of Loops Understanding Modules, Packages and Exception Handling Mastery in using libraries: Numpy, Pandas, Datetime, Matplotlib and Seaborn Gain pre-requisites to enter the world of AI, Machine Learning & Data Science This course is ideal for individuals who are Irrespective of what your age & background is, this is course is well suited for a Novice, Advanced Beginner, Competent, Proficient & an Expert or A zeal to solve problems is what Im looking for! It is particularly useful for Irrespective of what your age & background is, this is course is well suited for a Novice, Advanced Beginner, Competent, Proficient & an Expert or A zeal to solve problems is what Im looking for!.

Enroll now: Mastering Python: 0/1 -> 1/0 | Beginner to Advanced

Summary

Title: Mastering Python: 0/1 -> 1/0 | Beginner to Advanced

Price: $19.99

Average Rating: 4.6

Number of Lectures: 70

Number of Published Lectures: 70

Number of Curriculum Items: 70

Number of Published Curriculum Objects: 70

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Learn about various Data Structures in Python

Get introduced to Object Oriented Programming

Learn writing functions from scratch

Solving real-time use cases

Handling Numpy Arrays

Have an in-depth understanding of Loops

Understanding Modules, Packages and Exception Handling

Mastery in using libraries: Numpy, Pandas, Datetime, Matplotlib and Seaborn

Gain pre-requisites to enter the world of AI, Machine Learning & Data Science

Who Should Attend

Irrespective of what your age & background is, this is course is well suited for a Novice, Advanced Beginner, Competent, Proficient & an Expert

A zeal to solve problems is what Im looking for!

Target Audiences

Irrespective of what your age & background is, this is course is well suited for a Novice, Advanced Beginner, Competent, Proficient & an Expert

A zeal to solve problems is what Im looking for!

If you’re wondering who is this course for? Let me acquaint you!

This amazing course will be a guide to enhance the usage of Python for solving real-world problems!

This course presumes that you have no prior experience in programming. Having said that, you’ll be taught python from square one.

Irrespective of what your age & background is, this course is well suited for a Novice, Advanced Beginner, Competent, Proficient & an Expert who has the zeal to solve problems!

I’ll walk you through some amazing packages in Python and their applications, breaking the stereotypes and entering into a new world of programming. I’ll try to transform your preconceived notion about Python by taking it to the next level!

Unlike other programming paradigms, scripts written in python are readable, reliable, robust, and are reusable. This course gives a comprehensive and holistic view of python, by conveying concepts in a step by step manner which makes it easier for the learner to comprehend and fathom things, in and out.

Additionally, this course has assignments that must be solved after each section to promote Hands-On learning experience. Along with that, the course content is updated for free if any new concepts turn up.

Want to embrace, enlighten, and empower your skills with this course? Then let’s wave our hands!

Course Curriculum

Chapter 1: Course Introduction and Installation

Lecture 1: Course Glimpse

Lecture 2: Installing Python

Chapter 2: Basics of Programming

Lecture 1: Introduction to Python Programming

Lecture 2: Recap – Basics of Programming

Chapter 3: Lists and Tuples

Lecture 1: Introduction to Lists and Indexing

Lecture 2: List Functions

Lecture 3: List Cloning and Nested Lists

Lecture 4: Tuples

Lecture 5: Recap – Lists and Tuples

Chapter 4: Dictionaries and Sets

Lecture 1: Dictionary and its Functions

Lecture 2: Dictionaries and Sets

Lecture 3: Comparison and Logical Operators

Lecture 4: Recap – Dictionaries and Sets

Chapter 5: Conditional Statements

Lecture 1: If-Else Block Statements

Lecture 2: If-Else – Business Case – ATM Machine

Lecture 3: Recap – Conditional Statements

Chapter 6: Looping in Python – Basics to Advanced

Lecture 1: For Loop – Direct and Indirect Referencing

Lecture 2: For Loop – Break and Continue Keywords

Lecture 3: For Loop – Problem Solving – I

Lecture 4: For Loop – Problem Solving – II

Lecture 5: Data Structure Comprehensions

Lecture 6: While Loop – Introduction & Problem Solving

Lecture 7: Recap – Looping in Python – Basics to Advanced

Chapter 7: Creating User Defined Functions

Lecture 1: User-Defined Functions

Lecture 2: Functions – Problem Solving Exercise

Lecture 3: Functions – *Args and **Kwargs

Lecture 4: Anonymous Functions

Lecture 5: Recap – Creating User Defined Functions

Chapter 8: Numpy Arrays – I

Lecture 1: Introduction to Numpy Arrays

Lecture 2: Numpy Array Functions – I

Lecture 3: Numpy Array Functions – II

Lecture 4: Indexing and Broadcasting of Arrays

Lecture 5: Recap – Numpy Arrays – I

Chapter 9: Numpy Arrays – II

Lecture 1: Mathematical Operations Using Arrays

Lecture 2: Numpy – Random Module

Lecture 3: Arrays vs Lists – Optimization

Lecture 4: Introduction to Linalg Module

Lecture 5: Recap – Numpy Arrays – II

Chapter 10: Pandas – Series

Lecture 1: Series – Introduction and Indexing

Lecture 2: Recap – Pandas – Series

Chapter 11: Pandas – Data Frames – I

Lecture 1: Data Frames – Introduction and Manipulation

Lecture 2: Indexing of Data Frames – I

Lecture 3: Indexing of Data Frames – II

Lecture 4: Filtering of Data Frames

Lecture 5: Recap – Pandas – Data Frames – I

Chapter 12: Pandas – Data Frames – II

Lecture 1: Functions Applied on Data Frames

Lecture 2: Importing Files and Exploratory Data Analysis (EDA)

Lecture 3: Identifying and Dealing with Missing Values

Lecture 4: Merging of Data Frames

Lecture 5: Concatenation of Data Frames

Lecture 6: Data Frames – Exporting Files and Miscellaneous Functions

Lecture 7: Recap – Pandas – Data Frames – II

Chapter 13: Handling Strings

Lecture 1: Introduction to Strings and its Functions – I

Lecture 2: String Functions and Conversion – II

Lecture 3: Recap – Handling Strings

Chapter 14: Dealing with Dates and Time

Lecture 1: Dates in Python

Lecture 2: Creating Date-time Objects and Conversion

Lecture 3: Time Package

Lecture 4: Date-time Objects Using Pandas

Lecture 5: Recap – Dealing with Dates and Time

Chapter 15: Data Visualization Using Matplotlib and Seaborn

Lecture 1: Introduction to Matplotlib

Lecture 2: Sin-Cosine Curves and Scatter Plot

Lecture 3: Subplots Using Pyplot

Lecture 4: Subplots Using Figure Objects

Lecture 5: Adding Axes to Figure Objects and Bar Charts

Lecture 6: Histogram and Box Plots

Lecture 7: Data Visualization with Seaborn

Lecture 8: Recap – Data Visualization Using Matplotlib and Seaborn

Lecture 9: End of the Course!

Lecture 10: End of Course! (Optional)

Instructors

Sai Charan J
Data Scientist

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4 stars: 4 votes

5 stars: 5 votes

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