Crash course on Programming with Python 3
Learn extensive file handling - csv, json, pickling, gems of Python, data structures and Data Visualization techniques
Ratings 4.56 / 5.00
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
Description
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.
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