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    The Complete Machine Learning Bootcamp for Beginners 2025

    Posted By: lucky_aut
    The Complete Machine Learning Bootcamp for Beginners 2025

    The Complete Machine Learning Bootcamp for Beginners 2025
    Published 9/2025
    Duration: 12h 3m | .MP4 1920x1080 30 fps(r) | AAC, 44100 Hz, 2ch | 6.09 GB
    Genre: eLearning | Language: English

    Hands-On Machine Learning with Python, Data, and AI Tools for Beginners

    What you'll learn
    - Write Python code confidently using variables, loops, functions, and classes
    - Work with files, databases, and APIs to handle real-world data
    - Understand and apply core machine learning algorithms (regression, trees, clustering, PCA)
    - Train models on real datasets like housing, car prices, and health data
    - Build and deploy a machine learning project with Flask
    - Gain the foundation to move into deep learning, NLP, and advanced AI

    Requirements
    - No prior coding or math experience required — this course starts from the basics
    - A computer (Windows, macOS, or Linux) with internet access
    - Willingness to learn by coding along with the instructor
    - (Optional) Familiarity with basic math concepts like addition, subtraction, multiplication, and division will help, but is not mandatory
    - Curiosity about Python, AI, and how machine learning works in the real world

    Description
    TheMachine Learning Bootcamp for Complete Beginners 2025is the fastest way to start your journey into Python programming, data science, and machine learning—no prior experience required.

    We’ll start from the very basics of Python: data types, variables, loops, functions, classes, exceptions, file handling, and test-driven development. You’ll also work withdatabases and APIs, which are essential for handling real-world data.

    Once you’re confident with Python, we’ll dive into the heart ofmachine learning. Step by step, you’ll explore and apply key algorithms:

    Linear Regression– predicting house and car prices

    Logistic Regression– classifying health and customer data

    Decision Trees & Random Forests– modeling complex decisions

    KMeans Clustering– grouping unlabeled data

    PCA (Principal Component Analysis)– reducing dimensions for big data

    Finally, you’ll build and deploy acapstone project: aHouse Price Prediction web app with Flask, bringing everything you’ve learned into a practical, real-world project.

    This bootcamp focuses onhands-on coding, practical datasets, and real projectsso that you’re not just learning theory—you’re building skills you can use right away.

    Who Is This Course For?

    This course is designed for:

    Absolute beginners with no prior coding experience.

    Students or professionals curious about AI and machine learning.

    Career changers looking to enter the data science or AI field.

    Developers who want to strengthen their Python and ML foundations.

    Anyone who wants to understand how machine learning powers modern apps.

    What You Will Learn

    By the end of this bootcamp, you will:

    Write and test Python code confidently.

    Work with variables, functions, loops, classes, files, and databases.

    Fetch and process data from APIs.

    Apply core machine learning algorithms step by step.

    Train models with real datasets (housing, cars, customers, health).

    Build and deploy a machine learning app using Flask.

    Have a solid foundation to explore deep learning, NLP, and advanced AI.

    By enrolling today, you’ll gain lifetime access to the course, including future updates, downloadable resources, and hands-on projects—everything you need to break into machine learning in 2025.

    Who this course is for:
    - Absolute beginners who want to learn Python and machine learning from scratch
    - Students and professionals curious about data science and AI
    - Career changers looking to enter the fields of data science, machine learning, or analytics
    - Developers who want to strengthen their Python and ML foundations
    - Anyone interested in building real machine learning projects and web apps
    More Info