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Big Data Courses Online

Master big data technologies for handling large datasets. Learn about data storage, processing, and analysis using tools like Hadoop and Spark.

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Explore the Big Data Course Catalog

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Software Architecture for Big Data

    Skills you'll gain: Service Level, Software Engineering, Data Architecture, Web Applications, Software Architecture, Cloud Applications, Performance Testing, Scalability, Functional Requirement, Distributed Computing, Databases, Microservices, Application Deployment, Application Development, Predictive Modeling, Software Testing, System Design and Implementation, Middleware, Transaction Processing, Big Data

    Build toward a degree

    3.5
    Rating, 3.5 out of 5 stars
    ·
    101 reviews

    Advanced · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Streaming Big Data with Spark Streaming, Scala, and Spark 3!

    Skills you'll gain: Apache Kafka, Apache Spark, Scala Programming, Real Time Data, Apache Hadoop, Apache Cassandra, Applied Machine Learning, Big Data, Data Processing, Application Deployment, Distributed Computing, Development Environment

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Business Intelligence

    Skills you'll gain: Data Modeling, Stakeholder Engagement, Database Design, Dashboard, Business Intelligence, Extract, Transform, Load, Tableau Software, Data Warehousing, Data Pipelines, Data Integrity, Data Validation, Data-Driven Decision-Making, Data Visualization, Interviewing Skills, Business Process, Business Analysis, Professional Development, Google Gemini, Data Analysis, SQL

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    5.4K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Advanced Data Analytics

    Skills you'll gain: Data Storytelling, Data Visualization, Data Ethics, Exploratory Data Analysis, Sampling (Statistics), Data Presentation, Data Visualization Software, Regression Analysis, Feature Engineering, Descriptive Statistics, Statistical Hypothesis Testing, Advanced Analytics, Data Analysis, Tableau Software, Data Science, Statistical Analysis, Machine Learning, Object Oriented Programming (OOP), Interviewing Skills, Python Programming

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    9.1K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    DevOps, DataOps, MLOps

    Skills you'll gain: MLOps (Machine Learning Operations), Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Containerization, Tensorflow, Web Frameworks, Rust (Programming Language), Microsoft Copilot, DevOps, Cloud Solutions, CI/CD, Machine Learning, Serverless Computing, Docker (Software), GitHub, Command-Line Interface, Big Data

    4.2
    Rating, 4.2 out of 5 stars
    ·
    193 reviews

    Advanced · Course · 1 - 3 Months

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

    Packt

    Advanced Machine Learning, Big Data, and Deep Learning

    Skills you'll gain: Apache Spark, Keras (Neural Network Library), Deep Learning, Tensorflow, A/B Testing, Big Data, Data Ethics, Applied Machine Learning, Data Processing, Machine Learning Software, Artificial Neural Networks, Machine Learning Algorithms, Data Cleansing, Machine Learning, MLOps (Machine Learning Operations), Artificial Intelligence, Supervised Learning, Statistical Hypothesis Testing, Dimensionality Reduction, Reinforcement Learning

    Advanced · Course · 1 - 3 Months

What brings you to Coursera today?

  • Status: Preview
    Preview
    T

    The State University of New York

    Big Data, Genes, and Medicine

    Skills you'll gain: Bioinformatics, Big Data, Analytics, Data Mining, Health Informatics, Biomedical Technology, Data Processing, R Programming, Predictive Modeling, Statistical Analysis, Molecular Biology, Feature Engineering, Network Analysis, Unsupervised Learning

    4.2
    Rating, 4.2 out of 5 stars
    ·
    285 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Application Deployment, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    4.2
    Rating, 4.2 out of 5 stars
    ·
    518 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Enterprise Workflow

    Skills you'll gain: Feature Engineering, Data Ethics, Exploratory Data Analysis, Unsupervised Learning, Data Presentation, Tensorflow, Application Deployment, Dimensionality Reduction, MLOps (Machine Learning Operations), Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Visualization Software, Data Pipelines, Design Thinking, Unit Testing, Data Science, Machine Learning, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    348 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Science, Statistics, Probability Distribution, Mathematical Modeling, Data Analysis, Applied Mathematics, Predictive Modeling

    4.4
    Rating, 4.4 out of 5 stars
    ·
    777 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Foundations of Data Structures and Algorithms

    Skills you'll gain: Theoretical Computer Science, Algorithms, Data Structures, Graph Theory, Operations Research, Public Key Cryptography Standards (PKCS), Computational Thinking, Computer Programming, Programming Principles, Cryptography, Computer Science, Pseudocode, Applied Mathematics, Advanced Mathematics, Mathematical Theory & Analysis, Tree Maps, Encryption, Combinatorics, Python Programming, Analysis

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    865 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Software Architecture Patterns for Big Data

    Skills you'll gain: Performance Testing, Scalability, Data Architecture, Software Architecture, Distributed Computing, Predictive Modeling, Microservices, Big Data, Database Architecture and Administration, Test Case, Software Engineering, Application Performance Management, Data Store

    Build toward a degree

    3.6
    Rating, 3.6 out of 5 stars
    ·
    30 reviews

    Advanced · Course · 1 - 4 Weeks

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1234…29

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

  • Software Architecture for Big Data: University of Colorado Boulder
  • Streaming Big Data with Spark Streaming, Scala, and Spark 3!: Packt
  • Google Business Intelligence: Google
  • Google Advanced Data Analytics: Google
  • DevOps, DataOps, MLOps: Duke University
  • Advanced Machine Learning, Big Data, and Deep Learning: Packt
  • Big Data, Genes, and Medicine: The State University of New York
  • MLOps | Machine Learning Operations: Duke University
  • IBM AI Enterprise Workflow: IBM
  • Advanced Statistics for Data Science: Johns Hopkins University

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)

Frequently Asked Questions about Big Data

“Big data” is a term widely used to describe our data-rich world, in which virtually every activity generates a digital data footprint that can be collected and analyzed. While data and data analysis are not necessarily new, the effective use of the extremely large - and rapidly-growing - datasets of today require new approaches to data management.

In order to harness big data for important applications like machine learning and artificial intelligence, you need more than an Excel spreadsheet or a traditional relational database and SQL. Instead, an entire data infrastructure is necessary to collect and process this data at scale, including data pipelines, data lakes, and data warehouses.

To make this possible, data engineers rely on new approaches to data processing such as MapReduce, developed by Google, the open-source Apache Hadoop ecosystem including Apache Spark and Apache Hive, and, increasingly, cloud computing and cloud database platforms like Cloudera.‎

With companies in practically every industry eager to discover ways to harness the power of big data in their operations, having a background in this area can open doors to a wide range of careers. Operations managers at manufacturing or logistics companies may harness data to improve their demand forecasting, inventory planning, and process efficiency; digital marketers use marketing analytics to better understand their customers and the effectiveness of their messaging; and “quants” at hedge funds rely on data-based financial engineering approaches to move millions of dollars in milliseconds.

Understanding how big data applications are built and what they are capable of can thus be incredibly valuable even if you aren’t a data engineer or data scientist yourself. However, if you have the expertise and desire to work directly with big data yourself, data engineers are responsible for building the data infrastructure capable of reliably and efficiently delivering big data at scale, and data scientists are responsible for using a wide range of analytic and programming approaches to uncover insights from it.

These two roles are in extremely high demand, and command salaries to match. According to Glassdoor, data engineers earn an average annual salary of $102,864, and data scientists earn an average annual salary of $113,309.‎

Yes! In fact, Coursera is one of the best places to learn about big data. You can take individual courses and Specializations spanning multiple courses on big data, data science, and related topics from top-ranked universities from all over the world, from the University California San Diego to Universitat Autònoma de Barcelona. Coursera also offers the opportunity to learn from industry leaders in the field like Google, Cloudera, and IBM, including options to get professional certificates.‎

The skills and experience that you might need to already have before starting to learn big data may include software programming knowledge as well as top skills in math, algebra, data science, and related areas. The types of programming languages that are common in big data environments include Python, SQL, Java, C, and overall data structure and algorithm insights. Working with structured and unstructured data may likely require knowledge and background in discrete mathematics, statistics, and linear algebra. Of course, learning about big data roles would also require you to bring good soft skills like listening, focus, communication, and flexibility to the table. Finally, what would also play a part before starting to learn big data might include a good education in data science or mathematics.‎

The kind of people best suited for work that involves big data are those who are keenly interested in data sciences, statistical modeling, data analysis, and the move to a big data future with the internet. People who love to work with data are best suited for roles in big data. This would likely include persons who may have quantitative experience in data technology, or a background and a skill set working with accounting, finance, ratios, and percentages. Big data enthusiasts may also be adventurous types, who take big risks and want to work at the forefront of technology and society.‎

Learning big data may be right for you if you have strong analytical insights, a data science background, a head for numbers, and a familiarity with internet tools, cloud platforms, and data analysis software. Working in big data is one of the most in-demand jobs now, and the opportunity to work in a relevant field is very alluring. If you're flexible in your work roles, are a creative thinker, and have the discipline and right background, then learning big data may be right for you to advance your career forward.‎

Online Big Data courses offer a convenient and flexible way to enhance your existing knowledge or learn new Big Data skills. With a wide range of Big Data classes, you can conveniently learn at your own pace to advance your Big Data career skills.‎

When looking to enhance your workforce's skills in Big Data, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

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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