About Python training
Python Certification Training is not just a course; it’s a gateway to exciting career opportunities in fields such as Data Science, Internet of Things (IoT), scripting, and web application development. Python is renowned for its high reliability and simple syntax, making it an ideal programming language for both beginners and experienced developers.
Many leading companies, including YouTube, Dropbox, Instagram, Facebook, Google, Quora, Reddit, and Spotify, have all built their platforms using Python. By mastering this versatile language, you position yourself to work on innovative projects and be part of the tech-driven future. With the demand for Python skills continuously rising, investing in Python Certification Training can significantly enhance your career prospects.
Course Cirrculam
- Python Overview
- About Interpreted Languages
- Advantages/Disadvantages of Python pydoc
- Starting Python
- Interpreter PATH
- Using the Interpreter
- Running a Python Script
- Python Scripts on UNIX/Windows
- Python Editors and IDEs.
- Using Variables
- Keywords
- Strings Different Literals
- Math Operators and Expressions
- Writing to the Screen
- String Formatting
- Command Line Parameters and Flow Control
- Built-in Functions
- Lists
- Tuples
- Indexing and Slicing
- Iterating through a Sequence
- Functions for all Sequences
- Using Enumerate()
- Operators and Keywords for Sequences
- Dictionaries and Sets
- The xrange() function
- List Comprehensions
- Generator Expressions
- Functions
- Function Parameters
- Global Variables
- Variable Scope and Returning Values. Sorting
- Alternate Keys
- Lambda Functions
- Sorting Collections of Collections
- Sorting Dictionaries
- Sorting Lists in Place
- Errors and Exception Handling
- Handling Multiple Exceptions
- The Standard Exception Hierarchy
- Using Modules
- The Import Statement
- Module Search Path
- Package Installation Ways
- The Sys Module
- Interpreter Information
- STDIO
- Launching External Programs
- Paths Directories and Filenames
- Walking Directory Trees
- Math Function
- Random Numbers
- Dates and Times
- Zipped Archives
- Introduction to Python Classes
- Defining Classes
- Initializers
- Instance Methods
- Properties
- Class Methods and DataStatic Methods
- Private Methods and Inheritance
- Module Aliases and Regular Expressions.
- Debugging
- Dealing with Errors
- Using Unit Tests
- Project Skeleton
- Required Packages
- Creating the Skeleton
- Project Directory
- Final Directory Structure
- Testing your Setup
- Using the Skeleton
- Creating a Database with SQLite 3
- CRUD Operations
- Creating a Database Object
- Introduction to Machine Learning
- Areas of Implementation of Machine Learning
- Why Python
- Major Classes of Learning Algorithms
- Supervised vs Unsupervised Learning
- Learning NumPy
- Learning Scipy
- Basic plotting using Matplotlib
- Machine Learning application
- Classification Problem
- Classifying with k-Nearest Neighbours (kNN)
- Algorithm
- General Approach to kNN
- Building the Classifier from Scratch
- Testing the Classifier
- Measuring the Performance of the Classifier
- lustering Problem
- Introduction to Scikit-Learn
- Inbuilt Algorithms for Use
- What is Hadoop and why it is popular
- Distributed Computation and Functional Programming
- Understanding MapReduce Framework Sample
- Map Reduce Job Run
- PIG and HIVE Basics
- Streaming Feature in Hadoop
- Map Reduce Job Run using Python
- Writing a PIG UDF in Python
- Writing a HIVE UDF in Python
- Pydoop and MRjob Basics