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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


  • K

    King Abdullah University of Science and Technology

    Fundamental Skills in Bioinformatics

    Skills you'll gain: Statistical Analysis, Bioinformatics, Unix, Scientific Visualization, Statistical Programming, R (Software), Unix Shell, R Programming, Rmarkdown, Unix Commands, Data Analysis, Data Quality, Statistical Hypothesis Testing, Exploratory Data Analysis, Data Visualization, Data Cleansing, Programming Principles, Pandas (Python Package), Python Programming, NumPy

    ★ 4.4 (93) · Beginner · Course · 1 - 4 Weeks

  • D

    DeepLearning.AI

    Natural Language Processing with Probabilistic Models

    Skills you'll gain: Natural Language Processing, Markov Model, Embeddings, Data Preprocessing, Artificial Neural Networks, Machine Learning Methods, Algorithms, Data Cleansing, Probability & Statistics

    ★ 4.7 (1.8K) · Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    Vector Database Fundamentals

    Skills you'll gain: Vector Databases, Hugging Face, MongoDB, Embeddings, NoSQL, AI Personalization, Artificial Intelligence, PostgreSQL, Relational Databases, Database Management Systems, Generative AI, Operational Databases, SQL, Databases, Database Systems, LLM Application, Query Languages, Applied Machine Learning, Machine Learning, Data Science

    ★ 4.6 (74) · Intermediate · Specialization · 1 - 3 Months

  • I

    IBM

    Supervised Machine Learning: Classification

    Skills you'll gain: Classification Algorithms, Supervised Learning, Model Evaluation, Data Preprocessing, Logistic Regression, Machine Learning Algorithms, Decision Tree Learning, Applied Machine Learning, Model Training, Statistical Machine Learning, Predictive Modeling, Business Logic, Machine Learning Methods, Scikit Learn (Machine Learning Library), Data Cleansing, Machine Learning, Regression Analysis, Random Forest Algorithm, Model Optimization, Sampling (Statistics)

    ★ 4.8 (462) · Intermediate · Course · 1 - 3 Months

  • G

    Google Cloud

    Build, Train and Deploy ML Models with Keras on Google Cloud

    Skills you'll gain: Model Deployment, Tensorflow, Keras (Neural Network Library), Cloud Deployment, Google Cloud Platform, Data Pipelines, Model Training, Model Optimization, Deep Learning, Data Preprocessing, Artificial Neural Networks, Data Processing, Machine Learning, Python Programming, Data Transformation, Application Programming Interface (API)

    ★ 4.4 (2.8K) · Intermediate · Course · 1 - 3 Months

  • U

    University of Alberta

    Sample-based Learning Methods

    Skills you'll gain: Reinforcement Learning, Machine Learning Methods, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Applied Machine Learning, Probability Distribution

    ★ 4.8 (1.3K) · Intermediate · Course · 1 - 3 Months

  • U

    Universidad de los Andes

    Fundamentos de probabilidad y aplicaciones

    Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Applied Mathematics, Statistics, Risk Management, Risk Modeling, Combinatorics, Statistical Methods, Statistical Analysis, Variance Analysis

    ★ 4.8 (180) · Intermediate · Course · 1 - 4 Weeks

  • M

    Microsoft

    Microsoft Azure Machine Learning

    Skills you'll gain: Unsupervised Learning, Microsoft Azure, Applied Machine Learning, Machine Learning Software, Model Training, Regression Analysis, Predictive Modeling, Machine Learning, No-Code Development, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Model Deployment, Artificial Intelligence, Classification Algorithms, Supervised Learning

    ★ 4.4 (296) · Beginner · Course · 1 - 4 Weeks

  • I

    IBM

    AI Workflow: Enterprise Model Deployment

    Skills you'll gain: Model Deployment, Apache Spark, Data Pipelines, Cloud Deployment, Model Training, IBM Cloud, Applied Machine Learning, Machine Learning Methods, Model Optimization, Machine Learning Algorithms, Docker (Software), Machine Learning, Containerization, Data Science, Python Programming, Scalability, Design Thinking

    ★ 4.3 (62) · Advanced · Course · 1 - 4 Weeks

  • N

    National Taiwan University

    機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

    Skills you'll gain: Supervised Learning, Model Training, Machine Learning, Machine Learning Methods, Statistical Machine Learning, Model Evaluation, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Theoretical Computer Science, Classification Algorithms, Mathematical Modeling, Statistical Methods, Mathematical Theory & Analysis, Probability, Probability & Statistics, Algorithms

    ★ 4.9 (937) · Beginner · Course · 1 - 3 Months

  • I

    IBM

    AI Capstone Project with Deep Learning

    Skills you'll gain: Keras (Neural Network Library), Deep Learning, PyTorch (Machine Learning Library), Computer Vision, Machine Learning, Python Programming

    ★ 4.5 (695) · Advanced · Course · 1 - 4 Weeks

  • B

    Birla Institute of Technology & Science, Pilani

    Probability and Statistics

    Skills you'll gain: Data Analysis, Statistical Analysis, Statistical Methods, Analysis, Quantitative Research, Data Visualization, Predictive Modeling, Applied Mathematics

    ★ 4.1 (10) · Beginner · Course · 1 - 3 Months

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

  • Fundamental Skills in Bioinformatics: King Abdullah University of Science and Technology
  • Natural Language Processing with Probabilistic Models: DeepLearning.AI
  • Vector Database Fundamentals: IBM
  • Supervised Machine Learning: Classification: IBM
  • Build, Train and Deploy ML Models with Keras on Google Cloud: Google Cloud
  • Sample-based Learning Methods: University of Alberta
  • Fundamentos de probabilidad y aplicaciones: Universidad de los Andes
  • Microsoft Azure Machine Learning: Microsoft
  • AI Workflow: Enterprise Model Deployment: IBM
  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University

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