Python Core Advanced Training

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Python Core Advanced

This Python course assists users in mastering AI and machine learning technologies, as well as updating their abilities and understanding these languages. This Python training covers the fundamentals of Python, data operations, conditional expressions, shell scripting, and Django. This Python course will provide you with hands-on programming experience and prepare you for a lucrative career as a Python programmer

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Weeks Duration

Hr/Week Therory

Hr/Week Lab

Students per Batch

Core Python: 3 weeks

Week 1

Introduction to Python Programming

Introduction
Variables and Assignment Statements
Arithmetic
Function print and an Intro to Single- and Double-Quoted Strings
Triple-Quoted Strings
Getting Input from the User
Decision Making: The if Statement and Comparison Operators
Objects and Dynamic Typing
Intro to Data Science: Basic Descriptive Statistics

Control Statements and Program Development

Introduction
Algorithms
Pseudocode
Control Statements
if Statement
if…else and if…elif…else Statements
while Statement
for Statement: Iterables, Lists and Iterators & Built-In range Function
Augmented Assignments
Program Development: Sequence-Controlled Repetition: Requirements Statement,
Pseudocode for the Algorithm, Coding the Algorithm in Python & Introduction to
Formatted Strings
Program Development: Sentinel-Controlled Repetition
Program Development: Nested Control Statements
Built-In Function range: A Deeper Look
Using Type Decimal for Monetary Amounts
Break and continue Statements
Boolean Operators and, or and not
Intro to Data Science: Measures of Central Tendency—Mean, Median and Mode.

Functions

Introduction
Defining Functions
Functions with Multiple Parameters
Random-Number Generation
Case Study: A Game of Chance
Python Standard Library
math Module Functions
Using IPython Tab Completion for Discovery
Default Parameter Values
Keyword Arguments
Arbitrary Argument Lists
Methods: Functions That Belong to Objects
Scope Rules
import
Passing Arguments to Functions
Function-Call Stack
Functional-Style Programming
Intro to Data Science: Measures of Dispersion

Sequences: Lists and Tuples

Introduction
Lists
Tuples
Unpacking Sequences
Sequence Slicing
Del Statement
Passing Lists to Functions
Sorting Lists
Searching Sequences
Other List Methods
Simulating Stacks with Lists
List Comprehensions
Generator Expressions
Filter, Map and Reduce
Other Sequence Processing Functions
Two-Dimensional Lists
Intro to Data Science: Simulation and Static Visualizations

Week 2

Dictionaries and Sets

Introduction
Dictionaries: Creating a Dictionary, Iterating through a Dictionary, Basic Dictionary
Operations, Dictionary Methods keys and values, Dictionary Comparisons, Dictionary
Method update, & Dictionary Comprehensions
Sets: Comparing Sets, Mathematical Set Operations, Mutable Set Operators and
Methods, & Set Comprehensions
Intro to Data Science: Dynamic Visualizations

Array-Oriented Programming with NumPy

Introduction
Creating arrays from Existing Data
Array Attributes
Filling arrays with Specific Values
Creating arrays from Ranges
List vs. array Performance: Introducing %timeit
Array Operators
NumPy Calculation Methods
Universal Functions
Indexing and Slicing
Views: Shallow Copies
Deep Copies
Reshaping and Transposing
Intro to Data Science: pandas Series and DataFrames

Strings: A Deeper Look

Introduction
Formatting Strings: Presentation Types, Field Widths and Alignment, Numeric
Formatting, & String’s format Method
Concatenating and Repeating Strings
Stripping Whitespace from Strings
Changing Character Case
Comparison Operators for Strings
Searching for Substrings
Replacing Substrings
Splitting and Joining Strings
Characters and Character-Testing Methods
Raw Strings
Introduction to Regular Expressions: re Module and Function fullmatch, Replacing
Substrings and Splitting Strings, & Other Search Functions; Accessing Matches
Intro to Data Science: Pandas, Regular Expressions and Data Munging

Files and Exceptions

Introduction
Files
Text-File Processing: Writing to a Text File, Reading Data from a Text File
Updating Text Files
Serialization with JSON
Focus on Security: pickle Serialization and Deserialization
Additional Notes Regarding Files
Handling Exceptions: Division by Zero and Invalid Input, try Statements, Catching
Multiple Exceptions in One except Clause, What Exceptions Does a Function or
Method Raise?, & What Code Should Be Placed in a try Suite?
finally Clause
Explicitly Raising an Exception
(Optional) Stack Unwinding and Tracebacks
Intro to Data Science: Working with CSV Files

Week 3

Object-Oriented Programming

Introduction
A Custom Class: Composition: Object References as Members of Classes
Controlling Access to Attributes
Properties for Data Access
Simulating “Private” Attributes
Case Study: Card Shuffling and Dealing Simulations
Inheritance: Base Classes and Subclasses
Building an Inheritance Hierarchy; Introducing Polymorphism
Duck Typing and Polymorphism
Operator Overloading
Exception Class Hierarchy and Custom Exceptions
Named Tuples
A Brief Intro to Python 3.7’s New Data Classes: Creating a Data Class, Using the Data
Class, Data Class Advantages over Named Tuples, & Data Class Advantages over
Traditional Classes
Unit Testing with Docstrings and doctest
Namespaces and Scopes
Intro to Data Science: Time Series and Simple Linear Regression

Advanced Python: 3 weeks

Week 4

Starting Your Project

Laying Out Your Project
Version Numbering
Coding Style and Automated Checks

Modules, Libraries, and Frameworks

The Import System
Useful Standard Libraries
External Libraries
Package Installation: Getting More from pip
Using and Choosing Frameworks

Documentation and Good API Practice

Documenting with Sphinx

Handling Timestamps and Time Zones

The Problem of Missing Time Zones
Building Default datetime Objects
Time Zone–Aware Timestamps with dateutil
Serializing Time Zone–Aware datetime Objects
Solving Ambiguous Times

Week 5

Distributing Your Software

The setup.py History
Packaging with setup.cfg
The Wheel Format Distribution Standard
Sharing Your Work with the World
Entry Points

Unit Testing

The Basics of Testing
Virtual Environments
Testing Policy

Methods and Decorators

Decorators and When to Use Them
How Methods Work in Python
Static Methods
Class Methods
Abstract Methods
Mixing Static, Class, and Abstract Methods

Week 6

Functional Programming

Creating Pure Functions
Generators
List Comprehensions
Functional Functions Functioning

The Abstract Syntax Tree, Hy, and Lisp-like Attributes

Looking at the AST
Extending flake8 with AST Checks
Introduction to Hy

Performances and Optimizations

Data Structures
Understanding Behavior Through Profiling
Defining Functions Efficiently
Ordered Lists and bisect
namedtuple and Slots
Memoization
Faster Python with PyPy
Achieving Zero Copy with the Buffer Protocol

Scaling and Architecture

Multithreading in Python and Its Limitations
Multiprocessing vs. Multithreading
Event-Driven Architecture
Other Options and asyncio
Service-Oriented Architecture
Interprocess Communication with ZeroMQ

Managing Relational Databases

RDBMSs, ORMs, and When to Use Them
Database Backends
Streaming Data with Flask and PostgreSQL

Testimonial's

T. Aditya

I recommend this course to anyone looking to get into programming or those looking to sharpen their skills. I had zero experience with python before the course and the instructor was both patient enough to work with me yet still love the course flowing for the more advanced members

H. Varsha

The course was very comprehensive and easy to understand. The instructors made sure that they are giving the information in a way that won't make me confused. Thank you so much for this great course!

F. Darshini

Invictus has improved my practical skill in programming due a lot of practices and guidance. Taking Python core and advanced has really helped me gain confidence to take over so many programming challenges.

I. Arya

I did my Python Training in Hyderabad at Invictus. The Python Training Programme was good. My Python Mentor at Invictus gave us an in-depth training of the Python programming language and its application. Overall a very good training platform for the Python course. I will recommend Invictus to my friends.

A. Isaac

My learning experience at Invictus’s Python Training Program was excellent. Well-structured Python Course modules with regular assessment sessions helped me to understand the language at ease. Thanks to my Python trainer, nice work Invictus!