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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

    • S

      SkillUp EdTech

      Network Traffic Analysis with Wireshark

      Skills you'll gain:

      Intermediate · Course

    • M

      Microsoft

      R Programming Essentials with Microsoft Tools

      Skills you'll gain: Version Control, GitHub, Data Manipulation, Git (Version Control System), Software Documentation, Microsoft Development Tools, Microsoft Visual Studio, Microsoft Copilot, Data Import/Export, R Programming, Statistical Reporting, Statistical Analysis, Development Environment, Data Cleansing, Integrated Development Environments, Descriptive Statistics, Programming Principles, Debugging, Data Structures

      Beginner · Course · 1 - 3 Months

    • S

      SkillUp EdTech

      E-commerce and Email Marketing

      Skills you'll gain:

      Intermediate · Course

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 繁體中文

      Skills you'll gain: Generative AI, Google Cloud Platform, Big Data, Customer Relationship Management, SQL, Business Modeling, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 한국어

      Skills you'll gain: Generative AI, Customer Relationship Management, Workflow Management, Google Cloud Platform, Applied Machine Learning, Big Data, Business Modeling, Artificial Intelligence and Machine Learning (AI/ML), SQL, Predictive Modeling, Python Programming

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      G

      Google Cloud

      Introdução à análise de dados no Google Cloud

      Skills you'll gain:

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      G

      Google Cloud

      Google Cloud でのデータ分析の概要

      Skills you'll gain:

      Beginner · Course · 1 - 3 Months

    • U

      Universidad de los Andes

      Maestría en Inteligencia Artificial

      Skills you'll gain: Real-Time Operating Systems, Supervised Learning, Unsupervised Learning, Anomaly Detection, Computer Vision, Reinforcement Learning, Cloud-Native Computing, Natural Language Processing, Containerization, Deep Learning, Dimensionality Reduction, Artificial Intelligence, Machine Learning, CI/CD, Probability & Statistics, Control Systems, Data Ethics, Application Deployment, Epidemiology, Education Software and Technology

      Earn a degree

      Degree · 1 - 4 Years

    • G

      Google Cloud

      Gemini in Google Sheets - Français

      Skills you'll gain: Google Sheets, Google Workspace, Productivity Software, Generative AI, Project Management Software, Prompt Engineering, Data Management

      Beginner · Course · 1 - 4 Weeks

    • S

      SkillUp EdTech

      IT Systems Design and Analysis 

      Skills you'll gain:

      Intermediate · Course

    • G

      Google Cloud

      Responsible AI for Developers: Privacy & Safety - Italiano

      Skills you'll gain: Data Security, Generative AI, Information Privacy, Google Cloud Platform, Computer Security, Cloud Security, Security Controls, Application Security, Artificial Intelligence, Safety and Security

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Vector Search and Embeddings - 简体中文

      Skills you'll gain: Large Language Modeling, Text Mining, Google Cloud Platform, Natural Language Processing, Information Architecture, Applied Machine Learning, Algorithms

      Intermediate · Course · 1 - 4 Weeks

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

    • Network Traffic Analysis with Wireshark: SkillUp EdTech
    • R Programming Essentials with Microsoft Tools: Microsoft
    • E-commerce and Email Marketing : SkillUp EdTech
    • Work with Gemini Models in BigQuery - 繁體中文: Google Cloud
    • Work with Gemini Models in BigQuery - 한국어: Google Cloud
    • Introdução à análise de dados no Google Cloud : Google Cloud
    • Google Cloud でのデータ分析の概要 : Google Cloud
    • Maestría en Inteligencia Artificial: Universidad de los Andes
    • Gemini in Google Sheets - Français: Google Cloud
    • IT Systems Design and Analysis : SkillUp EdTech

    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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