Mastering Programming with Python 3

Mastering Programming with Python 3, available at $19.99, has an average rating of 4.6, with 44 lectures, based on 17 reviews, and has 35 subscribers.

You will learn about Learn Python programming from basics Confirm your learning by writing programs Become Proficient by carrying out the assignment Learn core Python 3 and Introduction to Data Structures Become thorough with file handling – CSV files, JSON, Pickling, text and binary files Learn the gems of Python – lambda functions, modules, Decorators, functional programming, namespaces and packages You will be able to face job interview successfully This course is ideal for individuals who are Students willing to Learn Python or Software developers who wish to brush up their knowledge in Python or Beginner Python developer curious about machine learning and data science or Students of all streams such as engineering, Science and computer applications who have taken Python as a subject or Persons interested in new jobs in Machine Learning and data science or Persons with Programming as a hobby It is particularly useful for Students willing to Learn Python or Software developers who wish to brush up their knowledge in Python or Beginner Python developer curious about machine learning and data science or Students of all streams such as engineering, Science and computer applications who have taken Python as a subject or Persons interested in new jobs in Machine Learning and data science or Persons with Programming as a hobby.

Enroll now: Mastering Programming with Python 3

Summary

Title: Mastering Programming with Python 3

Price: $19.99

Average Rating: 4.6

Number of Lectures: 44

Number of Published Lectures: 44

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

Learn Python programming from basics

Confirm your learning by writing programs

Become Proficient by carrying out the assignment

Learn core Python 3 and Introduction to Data Structures

Become thorough with file handling – CSV files, JSON, Pickling, text and binary files

Learn the gems of Python – lambda functions, modules, Decorators, functional programming, namespaces and packages

You will be able to face job interview successfully

Who Should Attend

Students willing to Learn Python

Software developers who wish to brush up their knowledge in Python

Beginner Python developer curious about machine learning and data science

Students of all streams such as engineering, Science and computer applications who have taken Python as a subject

Persons interested in new jobs in Machine Learning and data science

Persons with Programming as a hobby

Target Audiences

Students willing to Learn Python

Software developers who wish to brush up their knowledge in Python

Beginner Python developer curious about machine learning and data science

Students of all streams such as engineering, Science and computer applications who have taken Python as a subject

Persons interested in new jobs in Machine Learning and data science

Persons with Programming as a hobby

The course on Python 3 (core) is embedded with hundreds of tested program, 5 assignments and number of Case Studies.

The learners will gain immensely by using the Integrated DeveLopment Environment (IDLE) and Jupyter Notebook in Anaconda for executing the programs themselves.

It gives comprehensive and in-depth coverage of functions and recursions and tail recursion, in particular. The powerful features of Python containers such as lists, tuples, sets, and dictionaries are explained in an interesting manner.

Unicode-UTF-8, strings, selection and iteration concepts are explained with simplicity by executing programs. Python calculator and use of Mathematics and other libraries are illustrated.   

Python is also an object-oriented programming (OOP) language. The OOP concepts of inheritance and polymorphism, which facilitate seamless reuse of existing code as implemented in Python are discussed in a lucid manner.

Exceptions such as divide by zero might occur when we execute the programs. Python’s techniques of such exception handling are described with interesting case studies.

Python has many gems in terms of programming concepts such as decorator functions, lambda functions, function objects, and first-class functions, which are rather unique and thrilling and are discussed so that the student learns without even taking a break.

An introduction to data structures using Python is given. The section addresses stack and queue and also four popular sorting methods.

Data visualization must precede data analysis – predictive and descriptive. Python has excellent libraries for data visualization. An introduction to data visualization using pandas, matplotlib, and seaborn is given describing how to create a number of visuals.

The learning by programming and learning one new concept at a time in each program. is the strategy adopted so as to ease the burden of learning a new and modern programming language.

Course Curriculum

Chapter 1: M1 (1) -Introduction

Lecture 1: M1 Lesson 1 Introduction

Lecture 2: M1 Lesson 2 Python Calculator

Lecture 3: M1 Lesson 3 Built-in Library Functions

Lecture 4: M1 Lesson 4 Numerical Computations

Lecture 5: M1 Lesson 5 Console Input

Lecture 6: M1 Lesson 6 Unicode

Lecture 7: M1 Lesson 7 Strings

Lecture 8: M1 Lesson 8 String Methods

Lecture 9: Lesson 9 Console Output

Chapter 2: M1(2) – Functions & Recursion

Lecture 1: M1 Lesson 10 Selection Constructs

Lecture 2: M1 Lesson 11 Iterations

Lecture 3: M1 Lesson 12 Functions

Lecture 4: M1 Lesson 13 Fruitful Functions

Lecture 5: M1 Lesson 14 Recursion

Chapter 3: M2(1) Containers

Lecture 1: M2 Lesson 1 List Fundamentals

Lecture 2: M2 Lesson 2 List advanced

Lecture 3: M2 Lesson 3 List Case Studies

Lecture 4: M2 Lesson 4 Tuples

Lecture 5: M2 Lesson 5 Sets

Lecture 6: M2 Lesson 6 Dictionaries

Chapter 4: M2(2) Object Oriented Programming

Lecture 1: M2 Lesson 7 Object Oriented Programming

Lecture 2: M2 Lesson 8 Classes & Objects

Lecture 3: M2 Lesson 9 Operator overloading

Lecture 4: M2 Lesson 10 Containership

Lecture 5: M2 Lesson 11 Multi-level &Multiple Inheritance

Lecture 6: M2 Lesson 12 Polymorphism

Lecture 7: M2 Lesson 13 Iterators

Chapter 5: M3(1) File, and Exception handling

Lecture 1: M3 Lesson 1 Introduction to File Handling

Lecture 2: M3 Lesson 2 Text and Binary Files

Lecture 3: M3 Lesson 3 Traversing in a file

Lecture 4: M3 Lesson 4 JSON and Pickling

Lecture 5: M3 Lesson 5 Comma Separated Value (CSV) files

Lecture 6: M3 Lesson 6 Exception Handling Basics

Lecture 7: M3 Lesson 7 Advanced Exception Handling

Chapter 6: M3(2) Some Gems of Python

Lecture 1: M3 Lesson 8 Lambdas

Lecture 2: M3 Lesson 9 Modules

Lecture 3: M3 Lesson 10 Datetime Module

Lecture 4: M3 Lesson 11 Functional Programming

Lecture 5: M3 Lesson 12 Decorators, Namespaces and Packages

Chapter 7: M3(3) Introduction to Data Structures with Python

Lecture 1: M3 Lesson 13 Intro’ to Data Structures – Stack and Queue

Lecture 2: M3 Lesson 14 Sorting Data

Chapter 8: M3(4) Descriptive Analytics – Data Visualization

Lecture 1: M3 Lesson 15 Data Visualization

Lecture 2: M3 Lesson 16 Data Visualization with Pandas

Lecture 3: M3 Lesson 17 Data Visualization using Matplotlib and Seaborn

Instructors

Subburaj Ramasamy
Subburaj Academy

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2 stars: 0 votes

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4 stars: 1 votes

5 stars: 15 votes

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