Certification : Data Analytics Global Certification

Data analytics is a strategy-based science that involves analyzing raw data to find trends, answer questions, and draw conclusions. It uses tools and processes to combine and examine datasets to identify patterns and develop actionable insights.

Regular Courses | Fast Track Courses | Week End Courses
Course Duration

  • Fast Track : 1 Month
  • Regular Course : 3 Months
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    Course Advantages

  • Global Certificate
  • Latest Syllabus and Advanced Lab Facility
  • Provide hands-on experience with popular tools and programming languages such as Python,SQL, and data visualization tools like Power BI.
  • Course Features

  • Data analytics is a high-demand skill in various industries. Completing a data analytics course makes you valuable to employers seeking professionals with the ability to derive insights from data.
  • Data analytics skills open up a wide range of career opportunities in fields such as business, finance, healthcare, marketing, and technology. Many organizations are actively seeking professionals who can analyze and interpret data.
  • Organizations that leverage data analytics gain a competitive advantage. Individuals with data analytics skills contribute to this advantage by helping their employers stay ahead in a data-driven business landscape.
  • What you'll cover in this course

    Data Basics

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    Define the Concept of Data

    Describe Basic Data Variable Types

    Describe Basic Structure used in Data Analytics

    Describe Data Categories

    Data Manipulation

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    Import,Store,and Export Data

    Clean Data

    Organize Data

    Aggregate Data

    Data Analysis

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    Describe and Differentiate Between Types of Data Analysis

    Describe and Differentiate Between Data Aggregation and Interpretation Metrics

    Describe and Differentiate Between Exploratory Data Analysis Methods

    Evaluate and Explain the Results of Data Analyses

    Define and Describe the Role of Artificial Intelligence in Data Analysis

    Data Visualization and Communication

    + -

    Report Data

    Create Visualozations from Data

    Derive Conclusions from a Data Visualization

    Responsible Analytics Practices

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    Describe Data Privacy Laws and Best Practices

    Describe Best Practices for Responsible Data Handling

    Given a Scenario, Describe Types of Bias that Affect Collection and Interpretation of Data