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Instructor Name

Self Study

Category

Tech Development

Reviews

3 (17 Rating)

Course Requirements

Graduate / Working Professionals

Course Description

Big Data is a rapidly growing field that deals with the collection, storage, analysis, and visualization of large datasets. These datasets are so large that traditional data processing tools are inadequate to handle them efficiently.

The WBL Big Data course  covers the following topics:

  • What is Big Data? Understanding the characteristics of big data (volume, velocity, variety, veracity, and value)
  • Hadoop Ecosystem: Learning about the components of the Hadoop ecosystem, including Hadoop Distributed File System (HDFS), MapReduce, PIG and Hive
  • Machine Learning 
  • Using Power BI
  • Case Study: Retail Analytics 
  • Course Outcomes

     The WBL Big Data course can equip you with a wide range of valuable skills and knowledge. Here are some potential course outcomes:

    • Proficiency in Hadoop Ecosystem: Understanding the components of the Hadoop ecosystem, including HDFS, MapReduce and Yarn
    • Data Processing and Analysis Skills: Ability to use tools like Apache Spark, Pig, and Hive to process and analyze large datasets.
    • Machine Learning for Big Data: Understanding how to apply machine learning algorithms to extract insights from big data.
    • Real-time Analytics: Ability to analyze streaming data in real time for applications like fraud detection and customer churn analysis.

    Soft Skills

    • Problem-Solving: Improved ability to identify and solve complex problems related to big data.
    • Critical Thinking: Enhanced ability to analyze data and draw meaningful conclusions.
    • Communication: Stronger communication skills, including effective verbal and written communication.
    • Collaboration: Improved ability to work effectively with others in a team environment.

    Career Opportunities

    • Data Scientist: Analyzing data to discover insights and trends.
    • Data Engineer: Designing and building data pipelines and infrastructure.
    • Data Analyst: Collecting, cleaning, and analyzing data to support decision-making.
    • Business Intelligence Analyst: Using data to improve business performance.
    • Machine Learning Engineer: Developing and deploying machine learning models.

    By completing a Big Data course, you will be well-prepared to pursue a career in the field of big data and analytics. You will also gain valuable skills that can be applied to a variety of industries and roles.

    Course Curriculum

    1 Understanding Databases
    N/A


    1 Introduction to Data Analytics
    25 Min


    1 Big Data and Hadoop
    37 Min


    2 Machine Learning
    56 Min


    3 Industry Applications
    14 Min


    4 Big Data Learning Assessment [Quiz]
    N/A


    1 Introduction to Power BI
    16 Min


    2 Power BI Lesson 2
    8 Min


    3 Power BI Lesson 3
    7 Min


    4 Power BI Lesson 4
    10 Min


    5 Power BI Lesson 5
    14 Min


    1 Retail Analytics
    30 Min


    1. Big Data Student Manual

    Instructor

    Self Study

    3 Rating
    17 Reviews
    8314 Students
    62 Courses

    Self-studying is a useful tool to enhance any learning experience, and when mastered, students young and old reap the benefits. Whether applied to studying for an AP exam or exploring new material independently due to sheer curiosity, self-studying can lead to new opportunities academically and professionally. Remember to utilize the world around you! Technology has put knowledge at your fingertips, so take advantage of all the easily accessible and low-cost tools at your disposal.


    Self-study, when done correctly, is a very effective learning tool, so it can be helpful when used to prepare for a test or learn an entirely new subject matter on your own. Here are some tips for practicing successful self-studying:

    • Set realistic goals. Setting work goals for yourself, ones that realistically fit in with your life and other commitments, is important when creating self-study habits. You can set yourself up for success by assigning only a certain number of chapters to read each night, adjusting your workload according to how hectic your schedule is in any given week, and giving yourself a mental break each week to let your mind rest.
    • Find what works for you. There are many different ways to learn, and it is important to adjust studying techniques to find what works for your brain. Some students find reading aloud helpful, others like taking handwritten notes rather than typing. Discover whatever works best for you, and stick with it.
    • Review material the same day you learn it. After taking notes in an online course, or reading the next chapter in your textbook, make sure you review all the new material, by typing up your notes, practicing your new skill, or reading over a chapter again, to help it resonate. While this may seem tedious, it only takes a short amount of time. Reviewing can help with long-term absorption of material, so it decreases the need of cramming in the future.
    • Study in short, frequent sessions. Instead of treating your study session like a marathon, break up your material by topic into a series of short sessions, separated by short breaks. That way, you won’t be staring at your books or computer for too long while wearing on your focus, and your brain can absorb the material more easily. While cramming may seem like a great way to cover a lot of material in a condensed amount of time, studying in short, frequent sessions is a more effective way to learn subject matter and self-study.
    • Prepare and maintain your study environment. When learning remotely it is important to create a study space for yourself. By setting aside a desk or table that is a designated environment for self-studying or completing an online course, you will know to be mentally prepared to learn when you enter that space

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