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    • Big Data Analytics

    Big Data Analytics Courses Online

    Master big data analytics for processing and analyzing large datasets. Learn to use tools like Hadoop, Spark, and NoSQL databases.

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    Explore the Big Data Analytics Course Catalog

    • U

      University of California San Diego

      Big Data Modeling and Management Systems

      Skills you'll gain: Data Modeling, Big Data, Data Management, Database Management Systems, Real Time Data, NoSQL, Database Design, Apache Hadoop, Data Structures, Scalability, Virtual Environment

      4.4
      Rating, 4.4 out of 5 stars
      ·
      3K reviews

      Mixed · Course · 1 - 3 Months

    • M

      Macquarie University

      Excel Skills for Business

      Skills you'll gain: Microsoft Excel, Dashboard, Excel Formulas, Spreadsheet Software, Data Visualization, Excel Macros, Data Validation, Data Analysis Expressions (DAX), Data Cleansing, Data Modeling, Financial Forecasting, Predictive Modeling, Financial Modeling, Workflow Management, Finance, Data Management, Business Intelligence Software, Consolidation, Data Integrity, Data Entry

      4.9
      Rating, 4.9 out of 5 stars
      ·
      62K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM AI Product Manager

      Skills you'll gain: Prompt Engineering, Generative AI, New Product Development, Product Management, Product Lifecycle Management, Product Development, Innovation, Product Roadmaps, ChatGPT, Large Language Modeling, Product Planning, Commercialization, Product Strategy, Artificial Intelligence, Project Management Life Cycle, Data Ethics, OpenAI, Stakeholder Engagement, Stakeholder Management, Competitive Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      26K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • M

      Microsoft

      Harnessing the Power of Data with Power BI

      Skills you'll gain: Power BI, Data-Driven Decision-Making, Data Analysis, Data Collection, Business Intelligence, Analytical Skills, Data Transformation, Data Visualization Software, Microsoft 365

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      N

      Northeastern University

      Data Analytics Engineering: Probability & Techniques

      Skills you'll gain: Exploratory Data Analysis, Time Series Analysis and Forecasting, Data Analysis, Data Wrangling, Probability & Statistics, Unsupervised Learning, Text Mining, Data Manipulation, Statistical Analysis, Data Structures, Data Cleansing, Descriptive Statistics, Data Visualization Software, Python Programming

      Mixed · Course · 1 - 4 Weeks

    • G

      Google

      Foundations of Cybersecurity

      Skills you'll gain: Cybersecurity, Security Controls, Cyber Attacks, Security Management, Cyber Security Strategy, Incident Response, Cyber Risk, Security Information and Event Management (SIEM), Information Assurance, Data Ethics, Network Analysis, Ethical Standards And Conduct

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      34K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Pennsylvania

      AI Fundamentals for Non-Data Scientists

      Skills you'll gain: Generative AI, Big Data, Machine Learning, Customer Data Management, Tensorflow, Artificial Intelligence, Deep Learning, Algorithms, Process Optimization, Data Analysis, Artificial Neural Networks, Natural Language Processing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      720 reviews

      Mixed · Course · 1 - 3 Months

    • G

      Google

      Foundations of Digital Marketing and E-commerce

      Skills you'll gain: Data Storytelling, Customer experience strategy (CX), Performance Measurement, Data-Driven Decision-Making, E-Commerce, Marketing Strategies, Digital Marketing, Branding, Marketing Channel, Marketing Analytics, Search Engine Marketing, Search Engine Optimization, Social Media Marketing, Target Audience

      4.8
      Rating, 4.8 out of 5 stars
      ·
      28K reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Microsoft

      Data Modeling in Power BI

      Skills you'll gain: Data Analysis Expressions (DAX), Data Modeling, Star Schema, Power BI, Database Design, Data Transformation, Time Series Analysis and Forecasting, Performance Tuning

      4.3
      Rating, 4.3 out of 5 stars
      ·
      692 reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Python for Genomic Data Science

      Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Scripting Languages, Scripting, Data Processing, Computer Programming, Data Manipulation, File Management

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of California, Santa Cruz

      Bayesian Statistics: From Concept to Data Analysis

      Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • S

      Stanford University

      Graph Search, Shortest Paths, and Data Structures

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Network Model, Network Analysis, Computational Thinking, Theoretical Computer Science, Network Routing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Big Data Modeling and Management Systems: University of California San Diego
    • Excel Skills for Business: Macquarie University
    • IBM AI Product Manager: IBM
    • Harnessing the Power of Data with Power BI: Microsoft
    • Data Analytics Engineering: Probability & Techniques: Northeastern University
    • Foundations of Cybersecurity: Google
    • AI Fundamentals for Non-Data Scientists: University of Pennsylvania
    • Foundations of Digital Marketing and E-commerce: Google
    • Data Modeling in Power BI: Microsoft
    • Python for Genomic 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 Analytics

    Big data analytics refers to the application of advanced data analysis techniques to datasets that are very large, diverse (including structured and unstructured data), and often arriving in real time. The ability to process data at this scale is increasingly essential to navigating today’s business world, and it is at the core of important applications such as machine learning, business intelligence, financial engineering, and other software tools to enable data-informed decision-making.

    Computer programs have been used to assist with data analysis for decades, but tools like Microsoft Excel and traditional relational database management systems (RDBMS) queried with SQL are not capable of handling today’s high-volume, high-velocity datasets. Instead, today’s data management professionals rely on high-powered data infrastructure designed to work with distributed file systems and cloud computing resources - particularly the open-source Apache Hadoop ecosystem, including high-speed data processing with Apache Spark and distributed SQL engines like Apache Hive.‎

    Organizations of all types and sizes are seeking ways to leverage the possibilities of big data to improve operations through reduced costs and faster decision-making, create new products and services, or advance our knowledge about the world. Big data analytics skills can thus open up a wide range of career opportunities, from working as a “quant” on Wall Street to developing navigation systems for autonomous vehicles to helping to discover more effective medicines and drugs in health science.

    Two of the most broadly-applicable roles in this field are data engineers, who build the data infrastructure needed to deliver big data-scale datasets efficiently and reliably, and the data scientists responsible for analyzing them. These roles are in high demand, and are highly-paid as well; according to Glassdoor, data engineers earn an average annual salary of $102,864, and data scientists earn an average annual salary of $113,309.‎

    Absolutely! Data science is one of the most popular topics to learn about on Coursera, and there are a variety of options to build your skills in big data analytics. You can take online courses and Specializations from top-ranked schools like the University of Pennsylvania and the University of California San Diego, as well as leading companies like IBM, PwC, Cloudera, and Google Cloud. And regardless of where you choose to learn from, Coursera gives you the ability to access course materials and complete assignments on a flexible schedule, making this a great fit for students and mid-career professionals alike.‎

    Before you start learning big data analytics, it’s helpful to have an understanding of database management and the fundamentals of how programming languages work. Specifically, experience with SQL, Python, Java, or R can be useful when studying big data analytics. You also may find it beneficial to know how to work with Hadoop and Linux and use basic math and statistics. Additionally, strong analytical skills and a curiosity about playing with data come in handy when you learn big data analytics.‎

    The right people for roles in big data analytics are inquisitive problem solvers who like working with numbers and using statistics to sort through large amounts of data. They typically have work experience or coursework in high-level math or computer programming. A background in behavioral analysis can also be useful for roles in big data analytics because individuals often seek to understand or predict what influences the behavior represented by data. Big data analysts may often need soft skills, such as communication and collaboration skills they use when explaining what they see in the data and working with team members on projects.‎

    If you like working with numbers and are comfortable using statistical techniques, learning big data analytics may be right for you. The amount of data collected on a daily basis is already massive and continues to grow, so organizations need analysts who can curate and prepare data for businesses, governments, and other groups to use. Learning big data analytics may interest you if you possess strong analytical and problem-solving skills and want to apply those skills to sorting and analyzing data to find what’s useful for a client. You may be able to use the knowledge you gain to land an internship or seek a career in data science filling roles in a variety of industries.‎

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

    When looking to enhance your workforce's skills in Big Data Analytics, 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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