Python Training – Let Me Study

About Course

Python training provides individuals with a comprehensive understanding of the Python programming language, known for its simplicity and versatility. Participants learn Python’s syntax, data structures, and how to create efficient and readable code. Python training covers various applications, from web development and data analysis to automation and artificial intelligence. It often includes hands-on projects to reinforce learning. Python’s popularity in fields like data science and web development makes this training highly valuable for programmers, IT professionals, and aspiring developers. Python training equips learners with the skills to build software, analyze data, and solve a wide range of real-world problems efficiently.

Course Content

Module 01 – Python Environment Setup and Essentials

1.1 Introduction to Python Language
1.2 Features, the advantages of Python over other programming languages
1.3 Python installation – Windows, Mac & Linux distribution for Anaconda Python
1.4 Deploying Python IDE
1.5 Basic Python commands, data types, variables, keywords and more

Module 02 – Python language Basic Constructs

Module 03 – OOP concepts in Python

Module 04 – Database connection

Module 05 – NumPy for mathematical computing

Module 06 – SciPy for scientific computing

Module 07 – Matplotlib for data visualization

Module 08 – Pandas for data analysis and machine learning

Module 09 – Exception Handling

Module 10 – Multi Threading & Race Condition

Module 11 – Packages and Functions

Module 12 – Web scraping with Python

About Course

What Will You Learn?

Course Content

Module 01 – Python Environment Setup and Essentials

1.1 Introduction to Python Language

1.2 Features, the advantages of Python over other programming languages

1.3 Python installation – Windows, Mac & Linux distribution for Anaconda Python

1.4 Deploying Python IDE

1.5 Basic Python commands, data types, variables, keywords and more

Module 02 – Python language Basic Constructs

2.1 Built-in data types in Python

2.2 Learn classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug

2.3 Basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise

2.4 Loop and control statements while, for, if, break, else, continue.

Module 03 – OOP concepts in Python

3.1 How to write OOP concepts program in Python

3.2 Connecting to a database

3.3 Classes and objects in Python

3.4 OOPs paradigm, important concepts in OOP like polymorphism, inheritance, encapsulation

3.5 Python functions, return types and parameters

3.6 Lambda expressions

Module 04 – Database connection

4.1 Understanding the Database, need of database

4.2 Installing MySQL on windows

4.3 Understanding Database connection using Python

Module 05 – NumPy for mathematical computing

5.1 Introduction to arrays and matrices

5.2 Broadcasting of array math, indexing of array

5.3 Standard deviation, conditional probability, correlation and covariance.

Module 06 – SciPy for scientific computing

6.1 Introduction to SciPy

6.2 Functions building on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages, SciPy with Bayes Theorem

Module 07 – Matplotlib for data visualization

7.1 How to plot graph and chart with Python

7.2 Various aspects of line, scatter, bar, histogram, 3D, the API of MatPlotLib, subplots

Module 08 – Pandas for data analysis and machine learning

8.1 Introduction to Python dataframes

8.2 Importing data from JSON, CSV, Excel, SQL database, NumPy array to dataframe

8.3 Various data operations like selecting, filtering, sorting, viewing, joining, combining

Module 09 – Exception Handling

9.1 Introduction to Exception Handling

9.2 Scenarios in Exception Handling with its execution

9.3 Arithmetic exception

9.4 RAISE of Exception

9.5 What is Random List, running a Random list on Jupyter Notebook

9.6 Value Error in Exception Handling

Module 10 – Multi Threading & Race Condition

10.1 Introduction to Thread, need of threads

10.2 What are thread functions

10.3 Performing various operations on thread like joining a thread, starting a thread, enumeration in a thread

10.4 Creating a Multithread, finishing the multithreads.

10.5 Understanding Race Condition, lock and Synchronization.

Module 11 – Packages and Functions

11.1 Intro to modules in Python, need of modules

11.2 How to import modules in python

11.3 Locating a module, namespace and scoping

11.4 Arithmetic operations on Modules using a function

11.5 Intro to Search path, Global and local functions, filter functions

11.6 Python Packages, import in packages, various ways of accessing the packages

11.7 Decorators, Pointer assignments, and Xldr

Module 12 – Web scraping with Python

12.1 Introduction to web scraping in Python

12.2 Installing of beautifulsoup

12.3 Installing Python parser lxml

12.4 Various web scraping libraries, beautifulsoup, Scrapy Python packages

12.5 Creating soup object with input HTML

12.6 Searching of tree, full or partial parsing, output print