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  • Applied Data Science

Applied Data Science Courses

Applied Data Science courses can help you learn data analysis, statistical modeling, machine learning, and data visualization techniques. You can build skills in data cleaning, exploratory data analysis, and predictive analytics to derive insights from complex datasets. Many courses introduce tools like Python, R, and SQL, along with libraries such as Pandas and Scikit-learn, that support implementing data-driven solutions and automating processes in real-world applications.


More to explore:

Popular Applied Data Science Courses and Certifications


  • Status: Free Trial
    Free Trial
    G

    Google

    Google AI Essentials

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Generative AI, AI Enablement, AI Security, Risking, Artificial Intelligence and Machine Learning (AI/ML), AI Workflows, Model Evaluation, Process Optimization, Operational Efficiency, Emerging Technologies, Data Security, Critical Thinking, Analysis, Natural Language Processing, Innovation, Data-Driven Decision-Making

    4.8
    Rating, 4.8 out of 5 stars
    ·
    18K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    R

    Real Madrid Graduate School Universidad Europea

    How Did We Get Here?The Development of Analytics in Football

    Skills you'll gain: Analytics, Performance Analysis, Descriptive Analytics, Business Analytics, Data-Driven Decision-Making, Data Analysis, Media and Communications, Analysis, Predictive Analytics, Performance Measurement, Data Collection, Small Data, Big Data, Spatial Analysis, Research, Performance Reporting, Learning Styles, Innovation, Leadership, Communication

    Beginner · Course · 1 - 4 Weeks

  • C

    Coursera

    Support Vector Machines in Python, From Start to Finish

    Skills you'll gain: Scikit Learn (Machine Learning Library), Tensorflow, Classification Algorithms, Supervised Learning, Applied Machine Learning, Python Programming, Feature Engineering, Data Preprocessing, Data Science, Machine Learning, Model Evaluation, Data Manipulation, Data Visualization

    4.6
    Rating, 4.6 out of 5 stars
    ·
    161 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Preview
    Preview
    S

    SAS

    Statistical Thinking for Industrial Problem Solving, presented by JMP

    Skills you'll gain: Exploratory Data Analysis, Data Compilation, Correlation Analysis, Data Collection, Statistical Inference, Statistics, Statistical Methods, Statistical Modeling, Predictive Modeling, Data Analysis, Statistical Hypothesis Testing, Data-Driven Decision-Making, Regression Analysis, Statistical Analysis, Probability & Statistics, Descriptive Statistics, Data Visualization

    4.8
    Rating, 4.8 out of 5 stars
    ·
    99 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Natural Language Processing

    Skills you'll gain: Natural Language Processing, Supervised Learning, Transfer Learning, Recurrent Neural Networks (RNNs), Markov Model, Embeddings, Text Mining, Dimensionality Reduction, Machine Learning Methods, Statistical Machine Learning, Artificial Neural Networks, Classification Algorithms, Data Preprocessing, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Feature Engineering, Applied Machine Learning, Algorithms, Keras (Neural Network Library)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    6.2K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    SAS

    Getting Started with SAS Programming

    Skills you'll gain: SAS (Software), Data Import/Export, Data Access, Data Manipulation, Statistical Programming, Data Cleansing, Exploratory Data Analysis, Data Preprocessing, Data Analysis, Data Transformation, SQL, Microsoft Excel, Descriptive Statistics

    4.8
    Rating, 4.8 out of 5 stars
    ·
    3.2K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Preview
    Preview
    I

    IBM

    Machine Learning Introduction for Everyone

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning, Supervised Learning, Applied Machine Learning, Data Science, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    300 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California, Davis

    Fundamentals of Visualization with Tableau

    Skills you'll gain: Data Visualization, Interactive Data Visualization, Data Visualization Software, Data Presentation, Data Literacy, Data Ethics, Data Storytelling, Visualization (Computer Graphics), Dashboard, Tableau Software, Data Manipulation, Data Import/Export

    4.5
    Rating, 4.5 out of 5 stars
    ·
    6.8K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Structuring Machine Learning Projects

    Skills you'll gain: Transfer Learning, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Debugging, AI Product Strategy, Model Evaluation, Data-Driven Decision-Making, AI Workflows, Performance Tuning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    50K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Machine Learning

    Skills you'll gain: Autoencoders, Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Generative AI, Classification Algorithms, Regression Analysis, Dimensionality Reduction, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Artificial Intelligence and Machine Learning (AI/ML), Data Cleansing, Deep Learning, Data Science, Machine Learning, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.5K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Prompting Essentials

    Skills you'll gain: Data Visualization, Multimodal Prompts, Prompt Engineering, Data Presentation, Prompt Patterns, AI Enablement, AI Personalization, Generative AI, Email Automation, LLM Application, Data Analysis, Artificial Intelligence, Complex Problem Solving, Ideation, Business Correspondence, Report Writing, Solution Design, Critical Thinking, Document Management, Machine Learning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    5.7K reviews

    Beginner · Specialization · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Modeling and Predicting Climate Anomalies

    Skills you'll gain: Statistical Analysis, Matplotlib, Regression Analysis, Statistical Modeling, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Statistical Machine Learning, Machine Learning, Data Science, Environmental Policy, Data Analysis, Energy and Utilities, Data Visualization, Pandas (Python Package), Supervised Learning, Climate Change Mitigation, Anomaly Detection, Environment, Public Policies

    4.1
    Rating, 4.1 out of 5 stars
    ·
    7 reviews

    Intermediate · Specialization · 1 - 3 Months

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In summary, here are 10 of our most popular applied data science courses

  • Google AI Essentials: Google
  • How Did We Get Here?The Development of Analytics in Football: Real Madrid Graduate School Universidad Europea
  • Support Vector Machines in Python, From Start to Finish: Coursera
  • Statistical Thinking for Industrial Problem Solving, presented by JMP: SAS
  • Natural Language Processing: DeepLearning.AI
  • Getting Started with SAS Programming: SAS
  • Machine Learning Introduction for Everyone: IBM
  • Fundamentals of Visualization with Tableau: University of California, Davis
  • Structuring Machine Learning Projects: DeepLearning.AI
  • IBM Machine Learning: IBM

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