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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

    • Status: New
      New
      G

      Google Cloud

      Pengantar Analisis Data di Google Cloud

      Skills you'll gain:

      Beginner · Course · 1 - 3 Months

    • C

      Coursera

      Content Creation for TikTok, YouTube, Instagram, Facebook

      Skills you'll gain:

      Beginner · Professional Certificate · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Game Time 2024 – Build a JavaScript Game with Random Order

      Skills you'll gain: HTML and CSS, Ajax, Responsive Web Design, Cascading Style Sheets (CSS), Hypertext Markup Language (HTML), JSON, Javascript, Game Design, Animations, Debugging, Algorithms, Data Structures

      Intermediate · Course · 1 - 3 Months

    • M

      Microsoft

      Data Manipulation and Cleaning in R

      Skills you'll gain:

      Beginner · Course

    • C

      Coursera

      Creating Engaging Content for TikTok

      Skills you'll gain:

      Beginner · Course

    • O

      O.P. Jindal Global University

      MBA Business Analytics

      Skills you'll gain: Data Storytelling, Operations Management, Design Thinking, Active Listening, Data Visualization, Environmental Social And Corporate Governance (ESG), Working Capital, Database Management, Sampling (Statistics), Project Estimation, Business Analytics, Financial Statement Analysis, Global Marketing, Financial Accounting, Predictive Analytics, Big Data, Regression Analysis, Employee Performance Management, Marketing, Emerging Technologies

      Earn a degree

      Degree · 1 - 4 Years

    • Status: New
      New
      G

      Google Cloud

      Boost Productivity with Gemini in BigQuery - Indonesian

      Skills you'll gain: Exploratory Data Analysis, Google Cloud Platform, Data Wrangling, Interactive Data Visualization, Data Visualization, Generative AI, Debugging, SQL

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Interpretability & Transparency - Polski

      Skills you'll gain: Artificial Intelligence, Data Ethics, Data Analysis, Software Visualization, Exploratory Data Analysis, Technical Documentation, Applied Machine Learning, Machine Learning Methods, Machine Learning

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      A

      Amazon Web Services

      Amazon Connect: Introduction to the Administrative Interface

      Skills you'll gain: Dashboard, Report Writing, Business Reporting, Management Reporting, Performance Reporting, Ad Hoc Reporting, Real Time Data, Call Center Experience, Administration, Workforce Management

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Fairness & Bias - 日本語版

      Skills you'll gain: Data Ethics, Google Cloud Platform, Artificial Intelligence, Open Source Technology, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Data Quality, Data Analysis

      Intermediate · Course · 1 - 3 Months

    • M

      Microsoft

      Exploratory Data Analysis and Visualization

      Skills you'll gain:

      Beginner · Course

    • G

      Google Cloud

      Gemini in Google Sheets - Português Brasileiro

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

      Beginner · Course · 1 - 4 Weeks

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

    • Pengantar Analisis Data di Google Cloud: Google Cloud
    • Content Creation for TikTok, YouTube, Instagram, Facebook: Coursera
    • Game Time 2024 – Build a JavaScript Game with Random Order: Packt
    • Data Manipulation and Cleaning in R: Microsoft
    • Creating Engaging Content for TikTok: Coursera
    • MBA Business Analytics: O.P. Jindal Global University
    • Boost Productivity with Gemini in BigQuery - Indonesian: Google Cloud
    • Responsible AI for Developers: Interpretability & Transparency - Polski: Google Cloud
    • Amazon Connect: Introduction to the Administrative Interface: Amazon Web Services
    • Responsible AI for Developers: Fairness & Bias - 日本語版: Google Cloud

    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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