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Python Basic to Advanced Training

Python training, from basic to advanced levels, encompasses a comprehensive journey through the language's fundamentals, data structures, algorithms, and advanced concepts such as object-oriented programming, functional programming, and design patterns. Participants learn to leverage Python's versatility across various domains, including web development, data science, machine learning, and automation, gaining proficiency in libraries and frameworks like NumPy, pandas, Django, Flask, TensorFlow, and PyTorch. Through hands-on projects, exercises, and real-world applications, trainees develop the skills and intuition needed to solve complex problems efficiently and elegantly, making them adept Python developers equipped to tackle diverse challenges in today's technology landscape.

Introduction to Python Programming
Data Structures and Functions
Object-Oriented Programming (OOP)
Advanced Topics in Python
File Handling and Modules
Testing and Debugging
Advanced Python Libraries

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Course Highlights

Who should do this course?

The Python basic to advanced training course is suitable for a wide range of individuals, including:

This course fits best for:

Beginners:

Those who have little to no experience with programming and want to start with Python as their first language.

Students:

Both high school and college students who want to enhance their programming skills, whether for academic purposes or personal interest.

Professionals transitioning careers:

Individuals looking to switch to a career in software development or data science who need to learn Python as a fundamental skill.

Programmers in other languages:

Developers proficient in other programming languages who want to add Python to their skill set due to its versatility and popularity.

Data scientists and analysts:

Professionals working with data who want to leverage Python for data manipulation, analysis, and visualization using libraries like NumPy, Pandas, and Matplotlib.

Web developers:

Those interested in web development using frameworks like Django or Flask.

Automation engineers:

Professionals aiming to automate repetitive tasks or build scripts for system administration using Python.

Anyone interested in coding:

Individuals with a general interest in programming who want to learn Python for personal projects, hobbies, or just to broaden their knowledge.

Beginners:

Those who have little to no experience with programming and want to start with Python as their first language.

Students:

Both high school and college students who want to enhance their programming skills, whether for academic purposes or personal interest.

Professionals transitioning careers:

Individuals looking to switch to a career in software development or data science who need to learn Python as a fundamental skill.

Programmers in other languages:

Developers proficient in other programming languages who want to add Python to their skill set due to its versatility and popularity.

Data scientists and analysts:

Professionals working with data who want to leverage Python for data manipulation, analysis, and visualization using libraries like NumPy, Pandas, and Matplotlib.

Web developers:

Those interested in web development using frameworks like Django or Flask.

Automation engineers:

Professionals aiming to automate repetitive tasks or build scripts for system administration using Python.

Anyone interested in coding:

Individuals with a general interest in programming who want to learn Python for personal projects, hobbies, or just to broaden their knowledge.

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Course Curriculum

Sure, here's a sample curriculum for a Python training course that progresses from basic to advanced concepts:

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Material Valuation and Pricing

Integration with other SAP Modules

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Comprehensive Understanding

Hands-on Experience

Customization and Configuration

Integration with Other Modules

Reporting and Analytics

Python Basics

Introduction to Python

Variables and Data Types

Control Flow

Functions

Data Structures

Python Advanced

Meta programming

Concurrency and Parallelism

Performance Optimization

Advanced Data Structures and Algorithms

Functional Programming

Machine Learning

Deep Learning Advancements

Transfer Learning Dominance

AutoML Evolution

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Java

Basics of Java

Object-Oriented Programming (OOP)

Exception Handling

File Handling

Collections Framework

C++ Programming

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Object-Oriented Programming (OOP)

Standard Template Library (STL)

Memory Management

Exception Handling

C Programming

Introduction to C Programming Language

Basic Syntax and Structure

Memory Management

File Handling

Data Structures and Algorithms

ASP .NET

Framework Overview

Building Web Applications

Data Access and Management

Security Practices

Deployment and Hosting

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Introduction to Risk Management

Risk Management Framework

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Risk Assessment

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Six Sigma Green Belt

Introduction to Six Sigma

Define Phase

Measure Phase

Analyze Phase

Improve Phase

FIDIC

Introduction to FIDIC Contracts

Contractual Obligations and Rights

Risk Management in Contracts

Claims and Variations

Dispute Resolution

Fashion Designing

Introduction to Fashion Designing

Fashion Illustration and Sketching

Textile Science and Fabric Selection

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Fashion Trends and Forecasting