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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.


Popular Applied Data Science Courses and Certifications


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    EDUCBA

    Credit Default Prediction with Python: Apply & Analyze

    Skills you'll gain: Model Evaluation, Exploratory Data Analysis, Data Preprocessing, Predictive Modeling, Decision Tree Learning, Credit Risk, Random Forest Algorithm, Feature Engineering, Financial Modeling, Logistic Regression, Data Analysis, Statistical Machine Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Pandas (Python Package), Machine Learning Methods, Classification Algorithms

    Mixed · Course · 1 - 4 Weeks

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    University of California, Davis

    Tableau를 사용한 대시보드 및 스토리텔링 작성

    Skills you'll gain: Data Storytelling, Dashboard, Data Presentation, Interactive Data Visualization, Key Performance Indicators (KPIs), Tableau Software, Data Visualization Software, Data-Driven Decision-Making, Business Metrics, Data Quality

    Beginner · Course · 1 - 4 Weeks

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    DeepLearning.AI

    컨볼루션 신경망

    Skills you'll gain: Convolutional Neural Networks, Computer Vision, Image Analysis, Keras (Neural Network Library), Artificial Neural Networks, Tensorflow, Deep Learning, Transfer Learning, Applied Machine Learning, Classification Algorithms, Network Architecture

    Intermediate · Course · 1 - 4 Weeks

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    EDUCBA

    Machine Learning with R: Build, Analyze & Predict

    Skills you'll gain: Data Analysis, Statistical Analysis, Probability Distribution, R Programming, Exploratory Data Analysis, Statistical Modeling, Machine Learning, Statistical Inference, Classification Algorithms, Data Manipulation, Supervised Learning, Random Forest Algorithm, Regression Analysis, Model Evaluation, Decision Tree Learning

    4.6
    Rating, 4.6 out of 5 stars
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    14 reviews

    Mixed · Course · 1 - 4 Weeks

  • P

    Packt

    Financial Analysis with ARIMA and Time Series Forecasting

    Skills you'll gain: Time Series Analysis and Forecasting, Financial Forecasting, Statistical Analysis, Machine Learning, Trend Analysis, Financial Data, Financial Modeling, Jupyter, Predictive Modeling, GitHub, Statistical Modeling, NumPy

    Intermediate · Course · 1 - 3 Months

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    University of Colorado Boulder

    컴퓨터 비전 분야에서의 딥 러닝 응용 사례

    Skills you'll gain: Image Analysis, Tensorflow, Computer Vision, Convolutional Neural Networks, Applied Machine Learning, Deep Learning, Machine Learning, Artificial Neural Networks, Performance Tuning, Data Preprocessing, Model Evaluation, Feature Engineering, Algorithms

    Intermediate · Course · 1 - 3 Months

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    Coursera

    GenAI in Insurance: Automating Claims & Risk Mitigation

    Skills you'll gain: Generative AI, Insurance, AI Product Strategy, Responsible AI, Data Ethics, AI Enablement, Underwriting, AI Personalization, Operational Efficiency, Data-Driven Decision-Making, Claims Processing, Personalized Service, Artificial Intelligence, Automation, Risk Management, Analytics, Risk Mitigation, Prompt Engineering, Systems Integration

    Intermediate · Course · 1 - 4 Weeks

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    Johns Hopkins University

    R 프로그래밍

    Skills you'll gain: R Programming, Statistical Programming, Statistical Analysis, Data Analysis Software, Debugging, Software Installation, Simulations, Integrated Development Environments, Programming Principles, Data Manipulation, Program Development, Data Import/Export, Performance Tuning, File I/O

    Intermediate · Course · 1 - 4 Weeks

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    University of Washington

    머신 러닝 기초: 사례 연구 접근 방식

    Skills you'll gain: Model Evaluation, Regression Analysis, Applied Machine Learning, Machine Learning, Deep Learning, Jupyter, Supervised Learning, Predictive Analytics, Classification Algorithms, Image Analysis, Unsupervised Learning, Computer Vision, Text Mining, Natural Language Processing, Python Programming

    Mixed · Course · 1 - 3 Months

  • Status: Free
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    DeepLearning.AI

    Understanding and Applying Text Embeddings

    Skills you'll gain: Embeddings, LLM Application, Anomaly Detection, Generative AI, Google Cloud Platform, Natural Language Processing, Vector Databases, Semantic Web, Unsupervised Learning, Python Programming

    4.8
    Rating, 4.8 out of 5 stars
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    67 reviews

    Beginner · Project · Less Than 2 Hours

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    Khalifa University

    AI for Executives: AI for Business Decision Making

    Skills you'll gain: AI Enablement, Feature Engineering, Responsible AI, Data Preprocessing, Strategic Decision-Making, Business Leadership, Data-Driven Decision-Making, Data Ethics, Business Analytics, Natural Language Processing, Large Language Modeling, Artificial Intelligence, Predictive Analytics, Advanced Analytics, Governance, Data Governance, Systems Integration, Business Ethics, Workflow Management, Applied Machine Learning

    Beginner · Course · 1 - 4 Weeks

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    Coursera

    Creating Multi Task Models With Keras

    Skills you'll gain: Keras (Neural Network Library), Tensorflow, Convolutional Neural Networks, Deep Learning, Machine Learning, Computer Vision

    4.7
    Rating, 4.7 out of 5 stars
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    78 reviews

    Intermediate · Guided Project · Less Than 2 Hours

Searches related to applied data science

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

  • Credit Default Prediction with Python: Apply & Analyze: EDUCBA
  • Tableau를 사용한 대시보드 및 스토리텔링 작성: University of California, Davis
  • 컨볼루션 신경망: DeepLearning.AI
  • Machine Learning with R: Build, Analyze & Predict: EDUCBA
  • Financial Analysis with ARIMA and Time Series Forecasting: Packt
  • 컴퓨터 비전 분야에서의 딥 러닝 응용 사례: University of Colorado Boulder
  • GenAI in Insurance: Automating Claims & Risk Mitigation: Coursera
  • R 프로그래밍: Johns Hopkins University
  • 머신 러닝 기초: 사례 연구 접근 방식: University of Washington
  • Understanding and Applying Text Embeddings: DeepLearning.AI

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