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May 31, 2025

Data Science & AI Masters 2025 – From Python To Gen AI

4.502

2 Enrolled

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What Will I Learn?

Build a solid foundation in Python programming to effectively implement AI concepts and applications.
Learn how transformer models revolutionize NLP tasks, and how to leverage them for various applications.
Learn how to utilize vector databases for efficient storage and retrieval of embeddings in AI projects.
Explore the essentials of Large Language Models (LLMs) and their applications in generative tasks.
Learn how Machine Learning & Deep Learning works
Gain hands-on experience with Retrieval-Augmented Generation (RAG) and Langchain for building advanced AI applications.
Develop skills in crafting effective prompts to optimize model performance and achieve desired outputs.

Course Content

Introduction to Python

What is Python?
History and Evolution of Python
Features and Advantages of Python
Installing Python & Setting Up the Environment
Python IDEs (PyCharm, VS Code, Jupyter Notebook)
Writing and Executing First Python Program
Python File Extensions & Script Execution

Python Basics

Control Flow Statements

Python Data Structures

Functions in Python

Modules and Packages

Exception Handling

Object-Oriented Programming (OOP) in Python

File Handling

Multithreading & Multiprocessing

Python Standard Libraries & Utility Modules

Industry Best Practices & Advanced Topics

Introduction to AI

Mathematics for AI

Machine Learning Fundamentals

Deep Learning

AI Programming & Tools

Natural Language Processing (NLP)

Computer Vision

Reinforcement Learning

AI Ethics & Bias

AI in Industry Applications

AI Deployment & MLOps

Introduction to Machine Learning

Mathematics for ML

Data Processing & Feature Engineering

Supervised Learning

Unsupervised Learning

Neural Networks & Deep Learning

Reinforcement Learning

Model Deployment & MLOps

Industry-Specific ML Applications

Capstone Project & Case Studies

About the instructor

admin

4.50 (18 ratings)

7 Courses

2 students

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4.5

2 Reviews

11 months ago

Great starting point for learning Swift. If you have never programmed, or never used Swift it is a great place to start.

11 months ago

This course is amazing, it is extremely thorough and in depth.

Durations: 50 hours

Lectures: 149

Students: Max 0

Level: Intermediate

Language: English

Certificate: Yes

Material Includes

3.5 hours on-demand video
1 article
7 downloadable resources
Full lifetime access
Access on mobile and TV
Certificate of Completion

Requirements

Understand the value of building an Email List
Be interested in Affiliate Marketing
Have an Email Account

Audience

Anyone that is looking to make money with Email Marketing
Anyone that is looking to make money with Affiliate Marketing
Anyone that is interested in making money online
Anyone that wants to learn how to build a profitable business

Data Science & AI Masters 2025 – From Python To Gen AI

Data Science & AI Masters 2025 – From Python To Gen AI

What Will I Learn?

Course Content

Introduction to Python

What is Python?

History and Evolution of Python

Features and Advantages of Python

Installing Python & Setting Up the Environment

Python IDEs (PyCharm, VS Code, Jupyter Notebook)

Writing and Executing First Python Program

Python File Extensions & Script Execution

Python Basics

Python Syntax and Indentation

Variables and Data Types

Type Casting and Type Checking

Comments in Python

Input and Output Functions (print(), input())

Operators in Python (Arithmetic, Logical, Relational, Bitwise)

Control Flow Statements

Conditional Statements (if, if-else, if-elif-else)

Loops in Python (for, while, else with loops)

Loop Control Statements (break, continue, pass)

Python Data Structures

Lists (Operations, Methods, Slicing, List Comprehension)

Tuples (Properties, Indexing, Immutability)

Sets (Set Operations, Frozenset)

Dictionaries (Key-Value Pairs, Methods, Dictionary Comprehension)

Strings (String Methods, Formatting, Regular Expressions)

Functions in Python

Defining Functions (def, return, lambda)

Arguments and Parameters (Positional, Keyword, Default, *args, **kwargs)

Recursion in Python

Anonymous Functions (lambda, map(), filter(), reduce())

Modules and Packages

Importing Modules (import, from-import, as)

Standard Python Modules (math, datetime, os, sys, random)

Creating and Using Custom Modules

Python Packages (pip, Installing Third-Party Modules)

Exception Handling

Understanding Errors and Exceptions

Try, Except, Finally Blocks

Handling Multiple Exceptions

Custom Exceptions (raise, assert)

Object-Oriented Programming (OOP) in Python

Introduction to OOP Concepts

Defining Classes and Objects

Constructors (__init__())

Instance and Class Variables

Inheritance (Single, Multiple, Multilevel)

Method Overriding and Polymorphism

Encapsulation and Abstraction

Special (Dunder) Methods (__str__, __len__, __eq__)

File Handling

Reading and Writing Files (open(), read(), write())

Modes of File Handling (r, w, a, rb, wb)

Working with CSV and JSON Files

Exception Handling in File Operations

Multithreading & Multiprocessing

Threading vs Multiprocessing

Working with the threading Module

Synchronization in Threads

The multiprocessing Module for Parallel Execution

Python Standard Libraries & Utility Modules

Working with OS and File System (os, shutil, glob)

Date and Time Manipulation (datetime, time)

JSON and XML Processing (json, xml.etree.ElementTree)

Web Scraping with requests and BeautifulSoup

Logging and Debugging (logging)

Industry Best Practices & Advanced Topics

Writing Clean & Efficient Code (PEP 8 Guidelines)

Virtual Environments (venv, virtualenv)

Introduction to Unit Testing (unittest, pytest)

Debugging Python Code (pdb)

Introduction to Python Packaging (setuptools, wheel)

Introduction to AI

Definition and History of AI

Types of AI (Weak AI, Strong AI, General AI)

AI vs Machine Learning vs Deep Learning

Applications of AI in Various Industries

Constructors (init())

Special (Dunder) Methods (str, len, eq)