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Ivan Vega,
Joseph Lozada,
and
Daniel Roca
Learn the fundamentals of data analytics and how to apply them to real-world problems through Udacity’s Introduction to Data Analytics Online Training Course.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Excel
- Data visualization
- Chart types
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/7owxen/introduction
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What's inside
Syllabus
In this lesson, we will introduce you to data analysis and what we will be covering in this course.
In this lesson, we will learn how to solve data analysis issues using each step of the data analytics life cycle.
Read more
Syllabus
In this lesson, we will introduce you to data analysis and what we will be covering in this course.
In this lesson, we will learn how to solve data analysis issues using each step of the data analytics life cycle.
Read more
In this lesson, we will review the importance of data integrity in data analysis, the components of data integrity, and how to identify and fix it.
In this lesson, we will review each of the different types of data analytics and when to use them, along with statistics that pertain to each analytics type.
In this lesson, we will introduce Power BI and its capabilities as an analytics and data visualization tool.
In this project, you will use what you learned about data analytics to analyze KPIs for a company and represent your analysis with effective visuals.
In this lesson, you'll learn how to set up a Windows desktop workspace to use Power BI
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches data visualization, a highly relevant skill in many industries
Builds a strong foundation in data analytics for beginners
Uses Power BI, an industry-standard analytics and data visualization tool
Explores data integrity, an essential aspect of data analysis
Covers different types of data analytics, providing a comprehensive overview
Requires prior knowledge of Excel, data visualization, and chart types
Save this course
Save Introduction to Data Analytics to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Data Analytics with these
activities:
Review Statistical Concepts
Show steps
Sharpen your statistical knowledge to better grasp the analytical concepts covered in the course.
Browse courses on
Statistical Concepts
Show steps
-
Review probability distributions, sampling, and hypothesis testing.
-
Practice applying statistical techniques to real-world data.
Introduction to Data Analytics by McKinsey
Show steps
Gain a foundational understanding of data analytics principles and their practical applications.
View
Valuation, DCF Model Download: Measuring and...
on Amazon
Show steps
-
Read and comprehend the key concepts presented in the book.
-
Summarize and apply the principles to real-world data analytics scenarios.
Excel and Visualization Skills Practice
Show steps
Sharpen your Excel and data visualization skills to enhance your data analysis capabilities.
Browse courses on
Excel
Show steps
-
Practice creating and manipulating Excel spreadsheets.
-
Learn and apply different types of charts and graphs.
-
Create interactive visualizations using tools like Power BI.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Data Analytics Techniques Tutorial
Show steps
Learn various data analytics techniques and their applications.
Browse courses on
Data Analysis
Show steps
-
Identify the type of data and the appropriate analytics techniques to apply.
-
Gather and clean the data.
-
Perform data analysis using the chosen techniques.
-
Interpret the results and draw meaningful insights.
Data Analytics Study Group
Show steps
Enhance your understanding through discussions and collaboration with peers.
Show steps
-
Form a study group with other course participants.
-
Meet regularly to discuss the course material.
-
Share your perspectives and insights.
Data Analytics Workshop
Show steps
Attend a workshop to gain practical experience in data analytics tools and techniques.
Show steps
-
Research and identify relevant workshops.
-
Register and attend the workshop.
-
Actively participate in the hands-on exercises.
Data Analytics Project: Analyze Company KPIs
Show steps
Apply your data analytics skills to analyze real-world data and derive insights that drive decision-making.
Browse courses on
Key Performance Indicators
Show steps
-
Identify a company or dataset of interest.
-
Collect and clean the relevant data.
-
Analyze the data to identify key trends and patterns.
-
Develop visualizations and reports to present your findings.
-
Make recommendations based on your analysis.
Data Analytics Infographic
Show steps
Develop your data visualization skills by creating an infographic that summarizes key data analytics concepts.
Browse courses on
Data Visualization
Show steps
-
Gather and analyze the relevant data.
-
Choose an appropriate infographic design tool.
-
Create visually engaging and informative graphics.
-
Share your infographic with others.
Review Statistical Concepts
Show steps
Sharpen your statistical knowledge to better grasp the analytical concepts covered in the course.
Browse courses on
Statistical Concepts
Show steps
Show steps
Show steps
- Review probability distributions, sampling, and hypothesis testing.
- Practice applying statistical techniques to real-world data.
Introduction to Data Analytics by McKinsey
Show steps
Gain a foundational understanding of data analytics principles and their practical applications.
View
Valuation, DCF Model Download: Measuring and...
on Amazon
Show steps
Show steps
Show steps
- Read and comprehend the key concepts presented in the book.
- Summarize and apply the principles to real-world data analytics scenarios.
Excel and Visualization Skills Practice
Show steps
Sharpen your Excel and data visualization skills to enhance your data analysis capabilities.
Browse courses on
Excel
Show steps
Show steps
Show steps
- Practice creating and manipulating Excel spreadsheets.
- Learn and apply different types of charts and graphs.
- Create interactive visualizations using tools like Power BI.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Data Analytics Techniques Tutorial
Show steps
Learn various data analytics techniques and their applications.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify the type of data and the appropriate analytics techniques to apply.
- Gather and clean the data.
- Perform data analysis using the chosen techniques.
- Interpret the results and draw meaningful insights.
Data Analytics Study Group
Show steps
Enhance your understanding through discussions and collaboration with peers.
Show steps
Show steps
Show steps
- Form a study group with other course participants.
- Meet regularly to discuss the course material.
- Share your perspectives and insights.
Data Analytics Workshop
Show steps
Attend a workshop to gain practical experience in data analytics tools and techniques.
Show steps
Show steps
Show steps
- Research and identify relevant workshops.
- Register and attend the workshop.
- Actively participate in the hands-on exercises.
Data Analytics Project: Analyze Company KPIs
Show steps
Apply your data analytics skills to analyze real-world data and derive insights that drive decision-making.
Browse courses on
Key Performance Indicators
Show steps
Show steps
Show steps
- Identify a company or dataset of interest.
- Collect and clean the relevant data.
- Analyze the data to identify key trends and patterns.
- Develop visualizations and reports to present your findings.
- Make recommendations based on your analysis.
Data Analytics Infographic
Show steps
Develop your data visualization skills by creating an infographic that summarizes key data analytics concepts.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather and analyze the relevant data.
- Choose an appropriate infographic design tool.
- Create visually engaging and informative graphics.
- Share your infographic with others.
Career center
Learners who complete Introduction to Data Analytics will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst collects, transforms, and analyzes data in order to provide insights to stakeholders. This course, Introduction to Data Analytics, provides a solid foundation for a career as a Data Analyst, as it covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization. The course also provides hands-on experience with data analysis tools and techniques.
Business Analyst
Business Analyst
A Business Analyst uses data to identify and solve business problems. This course, Introduction to Data Analytics, can help Business Analysts develop the skills they need to analyze data, identify trends, and make recommendations to improve business performance. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Data Scientist
Data Scientist
A Data Scientist uses data to build models that can predict future outcomes. This course, Introduction to Data Analytics, can help Data Scientists develop the skills they need to collect, clean, and analyze data, and build predictive models. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Data Engineer
Data Engineer
A Data Engineer builds and maintains the infrastructure that is used to store and process data. This course, Introduction to Data Analytics, can help Data Engineers develop the skills they need to design and implement data pipelines, and manage data storage systems. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Statistician
Statistician
A Statistician uses data to design and conduct experiments, and analyze the results. This course, Introduction to Data Analytics, can help Statisticians develop the skills they need to collect, clean, and analyze data, and draw conclusions from the data. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Market Researcher
Market Researcher
A Market Researcher uses data to understand the needs and wants of consumers. This course, Introduction to Data Analytics, can help Market Researchers develop the skills they need to collect, clean, and analyze data, and identify trends in consumer behavior. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Financial Analyst
Financial Analyst
A Financial Analyst uses data to make investment decisions. This course, Introduction to Data Analytics, can help Financial Analysts develop the skills they need to collect, clean, and analyze financial data, and make recommendations on investment opportunities.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses data to improve the efficiency of business operations. This course, Introduction to Data Analytics, can help Operations Research Analysts develop the skills they need to collect, clean, and analyze data, and identify ways to improve business processes. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Actuary
Actuary
An Actuary uses data to assess risk and uncertainty. This course, Introduction to Data Analytics, can help Actuaries develop the skills they need to collect, clean, and analyze data, and develop models to assess risk.
Data Visualization Specialist
Data Visualization Specialist
A Data Visualization Specialist uses data to create visual representations of data. This course, Introduction to Data Analytics, can help Data Visualization Specialists develop the skills they need to collect, clean, and analyze data, and create visual representations of the data. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Computer Programmer
Computer Programmer
A Computer Programmer writes code to implement software applications. This course, Introduction to Data Analytics, may be helpful for Computer Programmers who want to develop their skills in data analysis. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course, Introduction to Data Analytics, may be helpful for Software Engineers who want to develop their skills in data analysis. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. This course, Introduction to Data Analytics, may be helpful for Database Administrators who want to develop their skills in data analysis. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Web Developer
Web Developer
A Web Developer designs and develops websites. This course, Introduction to Data Analytics, may be helpful for Web Developers who want to develop their skills in data analysis. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
Systems Analyst
Systems Analyst
A Systems Analyst analyzes and designs business systems. This course, Introduction to Data Analytics, may be helpful for Systems Analysts who want to develop their skills in data analysis. The course covers the fundamentals of data analytics, including data collection, data cleaning, data analysis, and data visualization.
For more career information including salaries, visit:
OpenCourser.com/course/7owxen/introduction
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Data Analytics.
Save
Comprehensive guide to data analytics, covering topics such as data collection, data cleaning, data visualization, and data analysis. It valuable resource for those who want to learn more about the field.
Focuses on using Microsoft Power BI for data analytics. It covers topics such as data import, data modeling, data visualization, and data analysis.
Save
Provides case studies of how data analytics is being used in various industries. It good resource for those who want to see how data analytics can be applied to real-world problems.
Provides a comprehensive overview of data analytics techniques and applications in finance. It good resource for those who want to learn more about data analytics in finance.
Save
Provides a comprehensive overview of big data analytics techniques and applications. It good resource for those who want to learn more about big data analytics.
Save
Provides a comprehensive overview of data analytics techniques and applications in marketing. It good resource for those who want to learn more about data analytics in marketing.
Provides a comprehensive overview of machine learning algorithms and techniques. It good resource for those who want to learn more about machine learning.
Save
Provides a comprehensive overview of deep learning algorithms and techniques. It good resource for those who want to learn more about deep learning.
Provides a comprehensive overview of data science techniques and applications. It good resource for those who want to learn more about data science.
Save
Covers the use of R for data mining. It covers topics such as data preprocessing, data mining algorithms, and data visualization.
Provides an overview of data analytics concepts and techniques, making it a good starting point for those new to the field. It covers topics such as data collection, cleaning, exploration, and visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/7owxen/introduction
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Effort
4 weeks
Level
Introductory
Via
Udacity
Instructors
Ivan Vega
Joseph Lozada
Daniel Roca
Language
English
Good to know
Teaches data visualization, a highly relevant skill in many industries
Builds a strong foundation in data analytics for beginners
Uses Power BI, an industry-standard analytics and data visualization tool
Explores data integrity, an essential aspect of data analysis
Covers different types of data analytics, providing a comprehensive overview
Requires prior knowledge of Excel, data visualization, and chart types
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