Live Python Training for Beginners

The Live Python Training course is for beginners. Meant as a private training, learning is easier when your trainer interacts with you in every class and answers doubts on the spot. All trainers for Live Python training for beginners are industry veterans. Join us for a free trial.

Live Course

Live Class: Thursday, 07 Mar

Duration: 24 Hours

Enrolled: 1

Offered by: infyni


Live Course


About Course

Python constantly levels as one of the most widespread programming languages.

This Live Python training for beginners is online and will train you in a very organized and structural way so that after completion of this course you are job-ready and be a professional in Python Programming.

Programming, as most people think is hard-coded language where prior knowledge of programming is required. But this is a very wrong interpretation. The good news is that it is not at all required to have any prior programming skills to learn Python. It is an easy language and you will be thrilled when you gradually learn it.

This live course will also give you the opportunity to start your career in Data Analyst / Data Science field. 

Unlike prerecorded sessions you will have interactive training. Take advantage of our special rates this summer and join us for a free trial. 

Skills You Will Gain

Database connectivity with Python File Handling Exception Handling String data type Control flow statements

Course Offerings

  • Instructor-led interactive classes
  • Clarify your doubts during class
  • Access recordings of the class
  • Attend on mobile or tablet
  • Live projects to practice
  • Case studies to learn from
  • Lifetime mentorship support
  • Industry specific curriculum
  • Certificate of completion
  • Employability opportunity
  • Topics
  • Instructor (1)
  • Reviews
  • Fundamental concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting
  • literals: Boolean, integer, floating-point numbers, scientific notation, strings
  • comments
  • the print() function
  • the input() function
  • numeral systems (binary, octal, decimal, hexadecimal
  • numeric operators
  • string operators
  • assignments and shortcut operators
  • Operators: unary and binary, priorities and binding
  • bitwise operators
  • Boolean operators: not and or
  • Boolean expressions
  • Relational operators, building complex Boolean expressions
  • accuracy of floating-point numbers
  • basic input and output operations using the input(), print(), int(), float(), str(), len() functions
  • formatting print() output with end= and sep= arguments
  • type casting
  • basic calculations
  • simple strings: constructing, assigning, indexing, slicing comparing, immutability
  • conditional statements: if, if-else, if-elif, if-elif-else
  • multiple conditional statements
  • the pass instruction
  • building loops: while, for, range(), in
  • iterating through sequences
  • expanding loops: while-else, for-else
  • nesting loops and conditional statements
  • controlling loop execution: break, continue
  • simple lists: constructing vectors, indexing and slicing, the len() function
  • lists in detail: indexing, slicing, basic methods (append(), insert(), index()) and functions (len(), sorted(), etc.), del instruction, iterating lists with the for loop, initializing, in and not in operators, list comprehension, copying and cloning
  • lists in lists: matrices and cubes
  • tuples: indexing, slicing, building, immutability
  • tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists
  • dictionaries: building, indexing, adding and removing keys, iterating through dictionaries as well as their keys and values, checking key existence, keys(), items() and values() methods
  • strings in detail
  • Defining and invoking your own functions
  • return keyword
  • the None keyword
  • recursion
  • parameters vs. arguments
  • positional keyword and mixed argument passing
  • default parameter values
  • Project 1 : Database management
  • Project 2 : Bank Application
  • lambda functions
  • map and filter functions
  • Recursive functions
  • Python modules and module namespace
  • import and from import
  • dir() and help() functions
  • Python packages and init py file
  • Introduction to files
  • File objects and modes
  • Opening and closing files
  • Read and write operations
  • Context manager - with
  • Directories and file path
  • os module
  • Making, changing and deleting directories
  • Listing directory and navigating file systems
  • Handling exceptions with - try, except, raise and assert
  • Causing exceptions with - raise and assert
  • Creating your own exception class
  • Working with CSV (comma separated value) files
  • What are xml files?
  • Making XML files with custom tags
  • XML parsing with etree
  • What is JSON?
  • JSON parsing - dump and load methods
  • Introduction to re module
  • Special characters for pattern making
  • re functions and flags
  • String matching and pattern filtering
  • Introduction to SQL database
  • Common SQL query
  • Connecting with sqlite3 database and making cursor object
  • Introduction to object oriented programming
  • Class variables and instance variables
  • Use of self and init ()
  • Class attributes
  • Object oriented programming techniques in python
  • Inheritance and types of inheritance
  • Overriding and overriding rules
  • Method overloading or polymorphism
  • Operator overloading
  • Introduction to threads
  • Creating and starting multiple threads
  • Project 1 : Data management with CSV files
  • Project 2 : Convert data from XML to CSV
  • Project 3 : Supermarket database management with regular expressions aeeza
  • Project 4 : MIS (Management Information System)


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