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  • Applied Machine Learning

Applied Machine Learning Courses

Applied Machine Learning courses can help you learn data preprocessing, model selection, feature engineering, and evaluation metrics. You can build skills in implementing algorithms, optimizing performance, and interpreting results in practical contexts. Many courses introduce tools like Python, TensorFlow, and scikit-learn, that support developing machine learning models and applying AI techniques to solve real-world problems.

Popular Applied Machine Learning Courses and Certifications


  • Status: Free Trial
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    E

    EDUCBA

    Deep Learning with Python: CNN, ANN & RNN

    Skills you'll gain: Model Evaluation, Convolutional Neural Networks, Model Training, Data Preprocessing, Image Analysis, Predictive Modeling, Deep Learning, Keras (Neural Network Library), Tensorflow, Data Processing, Model Optimization, Computer Vision, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Data Transformation, Financial Forecasting, Applied Machine Learning, Feature Engineering, Statistical Visualization, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    48 reviews

    Beginner · Specialization · 1 - 3 Months

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    W

    Whizlabs

    Fundamentals of Machine Learning

    Skills you'll gain: Supervised Learning, Unsupervised Learning, MLOps (Machine Learning Operations), Model Optimization, Applied Machine Learning, Machine Learning Methods, Model Evaluation, Model Training, Data Preprocessing, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Machine Learning Algorithms, Model Deployment, Microsoft Azure, Amazon Web Services, Data Mining, Cloud Solutions, Deep Learning, Data Processing

    Intermediate · Course · 1 - 3 Months

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    J

    Johns Hopkins University

    Foundational Mathematics for AI

    Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Data Analysis, Bayesian Statistics, Artificial Intelligence, Probability, Regression Analysis, Calculus, Mathematical Software, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Model Optimization, Integral Calculus, Algebra, Machine Learning Algorithms, Dimensionality Reduction

    4.9
    Rating, 4.9 out of 5 stars
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    11 reviews

    Beginner · Course · 1 - 3 Months

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    Coursera

    Databricks Machine Learning Quickstart

    Skills you'll gain: Databricks, Model Deployment, MLOps (Machine Learning Operations), Application Deployment, Model Training, Model Evaluation, Feature Engineering, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Performance Testing, AI Workflows, Machine Learning, System Monitoring, Security Controls

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Packt

    Machine Learning with R

    Skills you'll gain: Model Evaluation, Classification Algorithms, R Programming, Apache Spark, Deep Learning, Applied Machine Learning, Data Wrangling, Keras (Neural Network Library), Unsupervised Learning, Model Training, Data Manipulation, Machine Learning Algorithms, R (Software), Apache Hadoop, Data Science, Machine Learning, Tidyverse (R Package), Data Analysis, Bayesian Network, Logistic Regression

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Dartmouth College

    Foundations for Machine Learning

    Skills you'll gain: Probability & Statistics, Statistical Methods, Classification Algorithms, Calculus

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    Packt

    Core Machine Learning & Evaluation

    Skills you'll gain: Model Evaluation, Supervised Learning, Feature Engineering, Model Training, Applied Machine Learning, Machine Learning Methods, Model Optimization, Machine Learning, Machine Learning Algorithms, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Performance Tuning

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Machine Learning Engineer: ML and Deep Learning Models

    Skills you'll gain: Supervised Learning, Model Optimization, PyTorch (Machine Learning Library), Fine-tuning, Generative Model Architectures, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Generative AI, Deep Learning, Model Training, Applied Machine Learning, Statistical Machine Learning, Classification And Regression Tree (CART), Autoencoders, Machine Learning Methods, Machine Learning Software, Machine Learning, MLOps (Machine Learning Operations), Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML)

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
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    SAS

    Managing Machine Learning Models

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Model Training, Model Evaluation, Machine Learning Software, Process Modeling, Workflow Management, Predictive Modeling, Governance Risk Management and Compliance, SAS (Software), Text Mining, R Programming, Performance Analysis, Unstructured Data, Scheduling

    Intermediate · Course · 1 - 4 Weeks

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    Sage Publications

    AI and Machine Learning Essentials

    Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Responsible AI, Artificial Intelligence, Machine Learning Methods, Machine Learning, Computer Vision, Data Ethics, Automation, AI literacy, Applied Machine Learning, Natural Language Processing, Digital Transformation, Emerging Technologies, AI Integrations, Law, Regulation, and Compliance, Business Transformation

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    I

    Imperial College London

    Mathematics for Machine Learning: PCA

    Skills you'll gain: Dimensionality Reduction, NumPy, Unsupervised Learning, Statistical Methods, Descriptive Statistics, Jupyter, Statistics, Geometry, Linear Algebra, Data Transformation, Python Programming, Advanced Mathematics, Applied Mathematics, Calculus

    4
    Rating, 4 out of 5 stars
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    3.2K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    An Introduction to Learning Experience Design (LXD)

    Skills you'll gain: Program Evaluation, Course Development, Web Content Accessibility Guidelines, Educational Materials, Multimedia, Instructional Design, Learning Theory, Design, Design Thinking, Education Software and Technology, Professional Development, Brainstorming, Human Centered Design, Needs Assessment, Content Creation, Motivational Skills, Diversity Equity and Inclusion Initiatives, Prototyping, Design Strategies, Student-Centred Learning

    4.8
    Rating, 4.8 out of 5 stars
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    138 reviews

    Beginner · Specialization · 1 - 3 Months

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

  • Deep Learning with Python: CNN, ANN & RNN: EDUCBA
  • Fundamentals of Machine Learning: Whizlabs
  • Foundational Mathematics for AI: Johns Hopkins University
  • Databricks Machine Learning Quickstart: Coursera
  • Machine Learning with R: Packt
  • Foundations for Machine Learning: Dartmouth College
  • Core Machine Learning & Evaluation: Packt
  • Machine Learning Engineer: ML and Deep Learning Models: Coursera
  • Managing Machine Learning Models: SAS
  • AI and Machine Learning Essentials: Sage Publications

Skills you can learn in Machine Learning

Python Programming (33)
Tensorflow (32)
Deep Learning (30)
Artificial Neural Network (24)
Big Data (18)
Statistical Classification (17)
Reinforcement Learning (13)
Algebra (10)
Bayesian (10)
Linear Algebra (10)
Linear Regression (9)
Numpy (9)

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