Data Analytics Skills you will learn

  • Types of data analytics
  • Frequency distribution plots
  • Swarm plots
  • Data visualization
  • Data science methodologies
  • Analytics adoption frameworks
  • Trends in data analytics

Who should learn Data Analytics

  • Business or Data Analyst
  • Analytics Managers
  • Mid Level Managers
  • CXO

What you will learn in Data Analytics for Beginners 101

  • Introduction to Data Analytics

    • Lesson 1 - Course Introduction

      02:09
      • 1.01 Course Introduction
        02:09

    • Lesson 2 - Data Analytics Overview

      23:10
      • 2.01 Introduction
        00:35
      • 2.02 Data Analytics - Importance
        00:46
      • 2.03 Digital Analytics: Impact on Accounting
        03:08
      • 2.04 Data Analytics Overview
        02:33
      • 2.05 Types of Data Analytics
        00:42
      • 2.06 Descriptive Analytics
        00:57
      • 2.07 Diagnostic Analytics
        01:14
      • 2.08 Predictive Analytics
        01:16
      • 2.09 Prescriptive Analytics
        01:17
      • 2.10 Data Analytics - Amazon Example
        01:18
      • 2.11 Data Analytics Benefits Decision-Making
        01:27
      • 2.12 Data Analytics Benefits: Cost Reduction
        03:30
      • 2.13 Data Analytics Benefits: Amazon Example
        02:21
      • 2.14 Data Analytics: Other Benefits
        01:28
      • 2.15 Key Takeaways
        00:38

    • Lesson 3 - Dealing with Different Types of Data

      16:03
      • 3.1 Introduction
        00:29
      • 3.2 Terminologies in Data Analytics - Part One
        02:39
      • 3.3 Terminologies in Data Analytics - Part Two
        01:19
      • 3.4 Types of Data
        02:22
      • 3.5 Qualitative and Quantitative Data
        02:41
      • 3.6 Data Levels of Measurement
        02:56
      • 3.7 Normal Distribution of Data
        00:45
      • 3.8 Statistical Parameters
        02:35
      • 3.09 Key Takeaways
        00:17

    • Lesson 4 - Data Visualization for Decision making

      26:18
      • 4.1 Introduction
        00:25
      • 4.2 Data Visualization
        01:03
      • 4.3 Understanding Data Visualization
        02:57
      • 4.4 Commonly Used Visualizations
        02:27
      • 4.5 Frequency Distribution Plot
        01:35
      • 4.6 Swarm Plot
        01:23
      • 4.7 Importance of Data Visualization
        01:59
      • 4.8 Data Visualization Tools - Part One
        02:21
      • 4.9 Data Visualization Tools - Part Two
        01:49
      • 4.10 Languages and Libraries in Data Visualization
        02:09
      • 4.11 Dashboard Based Visualization
        03:01
      • 4.12 BI and Visualization Trends
        03:38
      • 4.13 BI Software Challenges
        01:01
      • 4.14 Key Takeaways
        00:30

    • Lesson 5 - Data Science, Data Analytics, and Machine Learning

      17:25
      • 5.01 Introduction
        00:27
      • 5.02 The Data Science Domain
        01:25
      • 5.03 Data Science, Data Analytics, and Machine Learning - Overlaps
        01:25
      • 5.04 Data Science Demystified
        02:50
      • 5.05 Data Science and Business Strategy
        02:18
      • 5.06 Successful Companies Using Data Science
        02:58
      • 5.7 Travel Industry
        01:16
      • 5.8 Retail
        00:47
      • 5.09 E-commerce and Crime agencies
        02:04
      • 5.10 Analytical Platforms across Industries
        01:23
      • 5.11 Key Takeaways
        00:32

    • Lesson 6 - Data Science Methodology

      09:15
      • 6.01 Introduction
        00:26
      • 6.02 Data Science Methodology
        01:20
      • 6.03 From Business Understanding to Analytic Approach
        01:02
      • 6.04 From Requirements to Collection
        01:06
      • 6.05 From Understanding to Preparation
        01:10
      • 6.06 From Modeling to Evaluation
        01:53
      • 6.07 From Deployment to Feedback
        01:52
      • 6.08 Key Takeaways
        00:26

    • Lesson 7 - Data Analytics in Different Sectors

      22:18
      • 7.01 Introduction
        00:33
      • 7.02 Analytics for Products or Services
        01:53
      • 7.03 How Google Uses Analytics
        02:30
      • 7.4 How LinkedIn Uses Analytics
        00:37
      • 7.05 How Amazon Uses Analytics
        02:03
      • 7.6 Netflix- Using Analytics to Drive Engagement
        00:56
      • 7.7 Netflix- Using Analytics to Drive Success
        02:49
      • 7.08 Media and Entertainment Industry
        01:10
      • 7.09 Education Industry
        02:57
      • 7.10 Healthcare Industry
        01:39
      • 7.11 Government
        02:31
      • 7.12 Weather Forecasting
        02:21
      • 7.13 Key Takeaways
        00:19

    • Lesson 8 - Analytics Framework and Latest trends

      13:00
      • 8.1 Introduction
        00:29
      • 8.2 Case Study: EY
        01:05
      • 8.3 Customer Analytics Framework
        00:59
      • 8.4 Data Understanding
        01:42
      • 8.5 Data Preparation
        00:50
      • 8.6 Modeling
        02:05
      • 8.7 Model Monitoring
        01:11
      • 8.8 Latest Trends in Data Analytics
        01:11
      • 8.9 Graph Analytics
        00:45
      • 8.10 Automated Machine Learning
        01:24
      • 8.11 Open Source AI
        00:52
      • 8.12 Key Takeaways
        00:27

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Why you should learn Data Analytics

$77.64 Billion

Market valuation by the end of 2023

CAGR of 30% from 2017-2023

Expected growth of Data Analytics market globally

Career Opportunities

FAQs

  • What are the prerequisites to learn Data Analytics?

    This Data Analytics free course can be taken without any prior knowledge of statistics or programming. However, a clear understanding of mathematics fundamentals is recommended before starting this program.

  • How do beginners learn Data Analytics?

    Beginners start with data analytics by learning the different types of data and how information is processed to draw meaningful conclusions from it. This data analytics free course can give you a complete overview of data analytics and how it is used.

  • How long does it take to learn Data Analytics?

    By going through the three hours of this informative data analytics introduction, you get an excellent start to your data analytics journey. Depending on the individual’s learning pace, it may take you around six months to learn data analytics.

  • What should I learn first in Data Analytics?

    For the field of data analytics, a good place to start is learning about different types of analytics and the various industrial sectors where data analytics is being adopted.

  • Is Data Analytics easy to learn?

    To learn data analytics, one should have a keen interest in dealing with data. With our data analytics free course, you can have a nearly effortless start in this field. 

  • What are the basics in the Data Analytics for beginners free course?

    Professionals beginning to learn data analytics usually have a basic understanding of mathematics, MS Excel, SQL, and the common terminologies used in data analytics.

  • What is Data Analytics used for?

    Companies are gathering a massive amount of information to make data-driven decisions and build quality products. Data analytics is the process through which raw data is gathered, preprocessed and analyzed to uncover hidden trends and patterns and assist the stakeholders in making the right decisions.

  • Why is Data Analytics so popular?

    Businesses across the world are embracing digital transformation and data-related roles have evolved since the past few years. The data that is generated from various resources is in the raw format and is only useful when analyzed effectively. As such data analytics has become quite popular for drawing invaluable insights and making good decisions. 

  • Why learn Data Analytics?

    You should learn Data Analytics because this technology has become a necessity in today’s data-driven world. Organizations view data analysis as one of the most crucial future specialties due to the value that can be derived from data. While 2.5 quintillion bytes of data are created each day, there aren’t enough data analysts to make sense of this enormous volume. This has led to an ever-increasing skill gap in data analytics and a surge in the demand for data analysts worldwide. Hence, the data analytics for beginners free course will help you get started on your learning journey.

  • What are the career opportunities in Data Analytics?

    Data-related job roles like data scientists, data analysts, and data architects are some of the most-sought-after career roles these days. Artificial Intelligence and machine learning applications have further fueled the need of data analytics. As such, companies are hiring data analysts and other professionals skilled in this field in large numbers.

  • Who can learn Data Analytics?

    Aspiring professionals of any educational background with an analytical frame of mind can learn data analytics. The data analytics for beginners free course is also best-suited for the following:

    • Students in UG/PG programs
    • IT professionals
    • Banking and finance professionals
    • Sales professionals
    • Beginners in the data analytics domain
       

  • Can I complete this Data Analytics free course in 90 days?

    Yes, this course can be completed within 90 days.

  • Will I get a certificate after completing the Data Analytics Introduction program?

    If you finish any free course on SkillUp within 90 days from the date of enrollment, you are eligible to receive a Course Completion Certificate for the same. Therefore, you will receive a shareable certificate on completing the Data Analytics Introduction program too. To unlock it, log in to your SkillUp account and click unlock. You will soon receive a mail with a link to the view and download the certificate. You can add the SkillUp certificate to your resume and share it on Facebook, LinkedIn etc.

  • What are my next best learning options after completing this Data Analytics course?

    One can take Data Scientist Master’s Program or Post Graduate Program in Data Analytics after completing this beginners course.

  • What are the career opportunities in Data Analytics?

    Data-related job roles like data scientists, data analysts, and data architects are some of the most-sought after career roles in this field. Artificial Intelligence and Machine Learning applications have further fueled the need of data analytics. As such, companies are hiring data analysts and other professionals skilled in this field in large numbers.    
     

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