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
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Subburaj Ramasamy
Subburaj Academy
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 1 votes
- 5 stars: 15 votes
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