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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

    • I

      IBM

      IBM Data Warehouse Engineer

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Linux Commands, Database Design, IBM Cognos Analytics, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Store, IBM DB2, Relational Databases, Dashboard, File Management, Stored Procedure

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Peer Review, Data Modeling, Relational Databases, Stored Procedure, Databases, Data Science, Big Data, Computer Programming Tools, Query Languages, Data Analysis Software, Data Cleansing, Data Visualization Software, GitHub, Business Analysis, Cloud Computing, Data Analysis

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      99K reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      Meta

      GenAI in Data Analytics

      Skills you'll gain: Generative AI, Business Analytics, Analytics, Data Quality, Business Analysis, Data Ethics, Prompt Engineering, Process Optimization, OpenAI, Artificial Intelligence, Data Analysis, ChatGPT, Machine Learning, Deep Learning, Natural Language Processing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      31 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California, Davis

      Health Information Literacy for Data Analytics

      Skills you'll gain: Data Governance, Data Quality, Data Integration, Data Dictionary, Data Validation, Health Informatics, Data Modeling, Extract, Transform, Load, Health Systems, Data Management, Metadata Management, Data Compilation, Analytics, Health Care, Data Mapping, Healthcare Industry Knowledge, Data Analysis, Data Cleansing, Health Information Management, Taxonomy

      4.5
      Rating, 4.5 out of 5 stars
      ·
      268 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Applied Data Science with Python

      Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Statistical Visualization, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      34K reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, Data Sharing, Statistical Reporting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Data Mining

      Skills you'll gain: Data Visualization Software, Text Mining, Data Presentation, Data Mining, Interactive Data Visualization, Data Storytelling, Dashboard, Tableau Software, Plot (Graphics), Natural Language Processing, Scatter Plots, Unsupervised Learning, Data Mapping, Unstructured Data, Statistical Analysis, Graphing, Big Data, Anomaly Detection, Analytics, Data Validation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Data Literacy, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      143K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of California, Davis

      Learn SQL Basics for Data Science

      Skills you'll gain: Data Governance, Presentations, Data Cleansing, Feature Engineering, SQL, Apache Spark, A/B Testing, Distributed Computing, Descriptive Statistics, Data Lakes, Data Quality, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Data Manipulation, Data Pipelines, Databricks, Database Design, Query Languages

      4.6
      Rating, 4.6 out of 5 stars
      ·
      17K reviews

      Beginner · Specialization · 3 - 6 Months

    • I
      U
      I

      Multiple educators

      Data Science Foundations

      Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Data Visualization Software, Correlation Analysis, Web Scraping, NumPy, Probability & Statistics, Predictive Modeling, Big Data, Computer Programming Tools, Automation, Data Analysis Software, Data Collection, Machine Learning Algorithms, Unsupervised Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      112K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Business Analyst

      Skills you'll gain: Data Storytelling, Requirements Elicitation, Risk Mitigation, Business Analysis, Business Process Modeling, Risk Analysis, Process Mapping, Process Optimization, Requirements Management, Risk Management, Business Requirements, Stakeholder Management, Work Breakdown Structure, Scope Management, Process Analysis, Stakeholder Engagement, Data Visualization Software, Excel Formulas, Microsoft Excel, Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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

    • IBM Data Warehouse Engineer: IBM
    • Introduction to Data Science: IBM
    • GenAI in Data Analytics: Meta
    • Health Information Literacy for Data Analytics: University of California, Davis
    • Applied Data Science with Python: University of Michigan
    • Data Science: Foundations using R: Johns Hopkins University
    • Meta Data Analyst: Meta
    • Data Mining: University of Illinois Urbana-Champaign
    • IBM Data Science: IBM
    • Learn SQL Basics for Data Science: University of California, Davis

    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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