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    • Big Data

    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

    • M

      Meta

      Programming with JavaScript

      Skills you'll gain: Jest (JavaScript Testing Framework), Web Development Tools, Javascript, Unit Testing, Web Applications, Programming Principles, Object Oriented Programming (OOP), Scripting Languages, Event-Driven Programming, Node.JS, Scripting, JSON, Computer Programming, Test Case, Data Structures, Debugging, Package and Software Management, Program Development, Development Environment, Functional Design

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

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      Status: New AI skills
      New AI skills
      A

      Adobe

      Adobe Marketing Specialist

      Skills you'll gain: Content Marketing, Color Theory, Promotional Strategies, Social Media Content, Target Audience, Typography, Color Matching, Digital Marketing, Marketing Communications, Content Creation, Generative AI, Customer experience strategy (CX), Graphic and Visual Design, Social Media Strategy, Marketing Strategies, Cross-Channel Marketing, Marketing Effectiveness, Prompt Engineering, Adobe Creative Cloud, Data Ethics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      762 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IE Business School

      Marketing Strategy

      Skills you'll gain: Survey Creation, Surveys, Marketing Planning, Market Research, Business Research, Product Marketing, Consumer Behaviour, Value Propositions, Market Analysis, Marketing, Business Planning, Marketing Channel, Peer Review, Product Strategy, Target Market, Research Design, Data Analysis, Marketing Strategies, Marketing Communications, Strategic Marketing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      D

      Duke University

      Oil & Gas Industry Operations and Markets

      Skills you'll gain: Market Dynamics, Energy and Utilities, Operating Cost, Transportation Operations, Production Process, Supply Chain, Market Data, Market Trend, Cost Estimation, Global Marketing, Market Analysis, International Finance, Natural Resource Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.2K reviews

      Mixed · Course · 1 - 4 Weeks

    • D

      Duke University

      AI Product Management

      Skills you'll gain: Deep Learning, MLOps (Machine Learning Operations), Data Ethics, Data Management, Unsupervised Learning, Human Computer Interaction, User Experience Design, Classification And Regression Tree (CART), Data Quality, Human Centered Design, Machine Learning, Human Factors, Regression Analysis, Technical Management, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Artificial Neural Networks, Decision Tree Learning, Data Processing, Personally Identifiable Information

      4.7
      Rating, 4.7 out of 5 stars
      ·
      779 reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      AI for Medicine

      Skills you'll gain: Deep Learning, Statistical Analysis, Clinical Trials, Feature Engineering, Risk Modeling, Treatment Planning, Data Analysis, Precision Medicine, Decision Tree Learning, Predictive Modeling, Patient Treatment, Image Analysis, Machine Learning Methods, Applied Machine Learning, AI Personalization, Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Intermediate · Specialization · 1 - 3 Months

    • D

      Duke University

      Introductory C Programming

      Skills you'll gain: Debugging, Maintainability, Programming Principles, Algorithms, Software Testing, Program Development, C (Programming Language), Pseudocode, Computational Thinking, Software Engineering, Simulations, System Programming, Data Structures, Software Development, Computer Programming, Command-Line Interface, Operating Systems, Development Environment, User Interface (UI), Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      P

      Pontificia Universidad Católica de Chile

      Introducción a la programación en Python I: Aprendiendo a programar con Python

      Skills you'll gain: Python Programming, Data Structures, Computer Programming, Program Development, Application Development, Algorithms, File Management

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.8K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      People Analytics

      Skills you'll gain: People Analytics, Human Resource Strategy, Talent Management, Workforce Planning, Organizational Effectiveness, Performance Analysis, Data-Driven Decision-Making, Workforce Management, Analytics, Performance Measurement, Employee Retention, Staff Management, Data Analysis, Predictive Analytics, Network Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Washington

      Machine Learning Foundations: A Case Study Approach

      Skills you'll gain: Applied Machine Learning, Feature Engineering, Regression Analysis, Machine Learning, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Artificial Intelligence, Deep Learning, Classification And Regression Tree (CART), Computer Vision, Application Development, Predictive Modeling, Natural Language Processing, Text Mining, Data Mining, Information Architecture

      4.6
      Rating, 4.6 out of 5 stars
      ·
      14K reviews

      Mixed · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Natural Language Processing with Classification and Vector Spaces

      Skills you'll gain: Natural Language Processing, Supervised Learning, Dimensionality Reduction, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Tensorflow, Linear Algebra, Probability & Statistics

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

      Intermediate · Course · 1 - 4 Weeks

    Big Data learners also search

    Big Data Analytics
    Beginner Big Data
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    Data Engineering
    Python Data Science
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    1…424344…597

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

    • Programming with JavaScript: Meta
    • Adobe Marketing Specialist: Adobe
    • Marketing Strategy: IE Business School
    • Reinforcement Learning: University of Alberta
    • Oil & Gas Industry Operations and Markets : Duke University
    • AI Product Management: Duke University
    • AI for Medicine: DeepLearning.AI
    • Introductory C Programming: Duke University
    • Introducción a la programación en Python I: Aprendiendo a programar con Python: Pontificia Universidad Católica de Chile
    • People Analytics: University of Pennsylvania

    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 Cloud, 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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