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  • Machine Learning Python

Results for "machine learning python"


  • Status: Free Trial
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    I

    IBM

    Machine Learning with Python

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Classification Algorithms, Feature Engineering

    4.7
    Rating, 4.7 out of 5 stars
    ·
    18K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Python for Data Science, AI & Development

    Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Application Programming Interface (API), Automation, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
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    43K reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    G

    Google

    Introduction to Data Analysis Using Python

    Skills you'll gain: Object Oriented Programming (OOP), Data Structures, Data Cleansing, Python Programming, Data Analysis, NumPy, Pandas (Python Package), Data Manipulation, Analytical Skills, Scripting, Algorithms, Debugging

    4.7
    Rating, 4.7 out of 5 stars
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    44 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D
    S

    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
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    38K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Machine Learning: Theory and Hands-on Practice with Python

    Skills you'll gain: Recurrent Neural Networks (RNNs), Vision Transformer (ViT), PyTorch (Machine Learning Library), Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Large Language Modeling, Natural Language Processing, Embeddings, Network Model, Network Architecture, Algorithms

    4.3
    Rating, 4.3 out of 5 stars
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    18 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Data Analysis with Python

    Skills you'll gain: Exploratory Data Analysis, Data Analysis, Data Import/Export, Data Manipulation, Data Transformation, Predictive Modeling, Data Cleansing, Data Preprocessing, Model Evaluation, Predictive Analytics, Pandas (Python Package), Regression Analysis, Feature Engineering, Statistical Analysis, Matplotlib, Scikit Learn (Machine Learning Library), Data Visualization, NumPy, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
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    20K reviews

    Intermediate · Course · 1 - 3 Months

What brings you to Coursera today?

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    D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Data Preprocessing, Machine Learning, Machine Learning Methods

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.2K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Supervised Machine Learning: Regression and Classification

    Skills you'll gain: Supervised Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Regression Analysis, Unsupervised Learning

    4.9
    Rating, 4.9 out of 5 stars
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    32K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Packt

    AI & Python Development Megaclass

    Skills you'll gain: Supervised Learning, Feature Engineering, Applied Machine Learning, Object Oriented Programming (OOP), Unsupervised Learning, Model Evaluation, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Transfer Learning, Machine Learning Algorithms, Data Visualization, Natural Language Processing, Seaborn, Predictive Modeling, Flask (Web Framework), Python Programming, Deep Learning, PyTorch (Machine Learning Library), Programming Principles, Web Applications

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    E

    EDHEC Business School

    Investment Management with Python and Machine Learning

    Skills you'll gain: Investment Management, Portfolio Management, Text Mining, Portfolio Risk, Asset Management, Network Analysis, Data Visualization Software, Investments, Machine Learning Methods, Return On Investment, Unstructured Data, Predictive Modeling, Web Scraping, Machine Learning, Social Network Analysis, Financial Statements, Applied Machine Learning, Financial Market, Financial Modeling, Risk Management

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.8K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Applied Machine Learning in Python

    Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
    ·
    8.8K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    L

    Logical Operations

    Using Data Science Tools in Python

    Skills you'll gain: Seaborn, NumPy, Matplotlib, Data Transformation, Data Manipulation, Data Visualization Software, Pandas (Python Package), Plot (Graphics), Data Visualization, Jupyter, Scatter Plots, Data Science, Data Processing, Data Analysis, Box Plots, Python Programming, Graphing, Computer Programming, Computer Programming Tools, Software Development

    Intermediate · Specialization · 1 - 3 Months

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In summary, here are 10 of our most popular machine learning python courses

  • Machine Learning with Python: IBM
  • Python for Data Science, AI & Development: IBM
  • Introduction to Data Analysis Using Python: Google
  • Machine Learning: DeepLearning.AI
  • Machine Learning: Theory and Hands-on Practice with Python: University of Colorado Boulder
  • Data Analysis with Python: IBM
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Supervised Machine Learning: Regression and Classification : DeepLearning.AI
  • AI & Python Development Megaclass: Packt
  • Investment Management with Python and Machine Learning: EDHEC Business School

Skills you can learn in Data Analysis

Analytics (85)
Big Data (64)
Python Programming (47)
Business Analytics (40)
R Programming (37)
Statistical Analysis (36)
Sql (33)
Data Model (29)
Data Mining (27)
Exploratory Data Analysis (26)
Data Modeling (21)
Data Manipulation (20)

Frequently Asked Questions about Machine Learning Python

Python machine learning is a subset of artificial intelligence that focuses on the development of algorithms that allow computers to learn from and make predictions based on data. It is important because it enables businesses and individuals to automate processes, gain insights from large datasets, and improve decision-making. As industries increasingly rely on data-driven strategies, proficiency in Python machine learning becomes a valuable asset for professionals looking to enhance their skills and career prospects.‎

With skills in Python machine learning, you can pursue a variety of roles in the tech industry and beyond. Common job titles include data scientist, machine learning engineer, AI researcher, and business analyst. These positions often involve analyzing data, developing predictive models, and implementing machine learning solutions to solve real-world problems. The demand for professionals with expertise in Python machine learning continues to grow, making it a promising career path.‎

To succeed in Python machine learning, you should develop a strong foundation in programming, particularly in Python. Key skills include understanding machine learning algorithms, data preprocessing, model evaluation, and data visualization. Familiarity with libraries such as NumPy, pandas, and scikit-learn is also essential. Additionally, a grasp of statistics and linear algebra will enhance your ability to understand and implement machine learning techniques effectively.‎

There are several excellent online courses available for learning Python machine learning. Some notable options include the AI and Machine Learning Essentials with Python Specialization and the Machine Learning: Theory and Hands-on Practice with Python Specialization. These courses provide a comprehensive introduction to the concepts and practical applications of machine learning using Python.‎

Yes. You can start learning Python machine learning on Coursera for free in two ways:

  1. Preview the first module of many Python machine learning courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in Python machine learning, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn Python machine learning, start by familiarizing yourself with the basics of Python programming. Once comfortable, explore online courses that cover machine learning concepts and techniques. Engage in hands-on projects to apply what you've learned, and utilize resources like tutorials and forums for additional support. Consistent practice and real-world application will help reinforce your understanding and build your confidence in this field.‎

Typical topics covered in Python machine learning courses include supervised and unsupervised learning, regression analysis, classification techniques, clustering, and neural networks. Courses often emphasize practical applications, such as data preprocessing, feature selection, and model evaluation. By exploring these topics, you will gain a well-rounded understanding of how to implement machine learning solutions effectively.‎

For training and upskilling employees or the workforce in Python machine learning, consider courses like the Applied Machine Learning with Python and the Machine Learning, Data Science and Generative AI with Python Specialization. These programs are designed to equip learners with practical skills and knowledge that can be directly applied in the workplace.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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