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Attendees will gain a step-by-step blueprint for building a data analytics academy, making the case to management, to identifying candidates and topics, to measuring its effectiveness.
Read more
Attendees will gain a step-by-step blueprint for building a data analytics academy, making the case to management, to identifying candidates and topics, to measuring its effectiveness.
Read more
Attendees will gain a step-by-step blueprint for building a data analytics academy, making the case to management, to identifying candidates and topics, to measuring its effectiveness.
In September 2019, McKinsey called for the rise of the in-house “analytics academy” to up-skill employees’ data literacy and prepare organizations for the changes from artificial intelligence and automation.
In this session, I will share tips for designing effective data analytics training programs acquired from working with leading technology and development organizations.
Attendees will gain a step-by-step blueprint for building a data analytics academy, making the case to management, to identifying candidates and topics, to measuring its effectiveness.
Register for this course and see more details by visiting:
OpenCourser.com/course/5zudjb/building
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What's inside
Syllabus
Building the Data Academy
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Addresses growing demand from organizations for employees who are data analytics literate
In-house training helps organizations prepare for AI and automation changes
Provides tips for designing effective training programs
Save this course
Save Building the Data Academy 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 Building the Data Academy with these
activities:
Read 'Data Science for Business'
Show steps
Gain valuable insights into how data science can be applied to solve business problems.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
-
Read the book and take notes on key concepts
-
Identify real-world examples of how data science is used in different industries
Review Intermediate SQL
Show steps
Warm up your SQL skills by reviewing the basics of Intermediate SQL.
Browse courses on
SQL
Show steps
-
Revisit SELECT statements, joins, and subqueries.
-
Practice writing queries to aggregate and manipulate data using GROUP BY, HAVING, and window functions.
-
Review how to use indexes and optimize query performance.
Organize and review course materials
Show steps
Reinforce your understanding of the course material by organizing and reviewing your notes, assignments, and quizzes.
Show steps
-
Gather all of your course materials
-
Organize your materials into a logical structure
-
Review your materials regularly
Six other activities
Expand to see all activities and additional details
Show all nine activities
Complete coding exercises from Pluralsight
Show steps
Practice and apply the concepts learned in the course by completing coding exercises provided on Pluralsight.
Show steps
-
Identify the coding exercise that aligns with the lesson topic.
-
Attempt to solve the exercise on your own.
-
Review the provided solution and compare your approach.
Complete Leetcode-style coding problems related to data structures and algorithms
Show steps
Solidify your understanding of data structures and algorithms by solving coding problems.
Show steps
-
Start with easier problems and gradually increase the difficulty.
-
Focus on understanding the problem statement and coming up with an efficient solution.
-
Implement your solution in a coding language of your choice and test it thoroughly.
-
Review your solution and identify areas for improvement.
Identify and connect with experienced professionals in the field
Show steps
Expand your network and gain guidance from those already working in the data analytics industry.
Show steps
-
Attend industry events and conferences
-
Reach out to your alumni network and professional organizations
-
Request informational interviews with individuals who work in roles you are interested in
Attend Coursera's 'Introduction to Data Analysis with R'
Show steps
Gain a comprehensive understanding of data analysis techniques by completing this Coursera course.
Show steps
-
Enroll in the course and complete the video lectures
-
Follow along with the hands-on exercises and assignments
-
Participate in the discussion forums to interact with peers and ask questions
Build a data visualization dashboard using Tableau or Power BI
Show steps
Develop your data visualization skills by creating a dashboard that communicates insights from a dataset.
Show steps
-
Choose a dataset that you are interested in
-
Identify the key insights that you want to communicate with your dashboard
-
Select appropriate charts and graphs to represent the data
-
Build and iterate on your dashboard until you are satisfied with the results
Participate in a Kaggle competition related to data analytics
Show steps
Challenge yourself and apply your skills by participating in a data analytics competition.
Show steps
-
Identify a Kaggle competition that aligns with your interests
-
Form a team or work individually on the competition
-
Develop and implement a data analytics solution
-
Submit your solution and track your progress on the leaderboard
Read 'Data Science for Business'
Show steps
Gain valuable insights into how data science can be applied to solve business problems.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
Show steps
Show steps
- Read the book and take notes on key concepts
- Identify real-world examples of how data science is used in different industries
Review Intermediate SQL
Show steps
Warm up your SQL skills by reviewing the basics of Intermediate SQL.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Revisit SELECT statements, joins, and subqueries.
- Practice writing queries to aggregate and manipulate data using GROUP BY, HAVING, and window functions.
- Review how to use indexes and optimize query performance.
Organize and review course materials
Show steps
Reinforce your understanding of the course material by organizing and reviewing your notes, assignments, and quizzes.
Show steps
Show steps
Show steps
- Gather all of your course materials
- Organize your materials into a logical structure
- Review your materials regularly
Six other activities
Expand to see all activities and additional details
Show all nine activities
Complete coding exercises from Pluralsight
Show steps
Practice and apply the concepts learned in the course by completing coding exercises provided on Pluralsight.
Show steps
Show steps
Show steps
- Identify the coding exercise that aligns with the lesson topic.
- Attempt to solve the exercise on your own.
- Review the provided solution and compare your approach.
Complete Leetcode-style coding problems related to data structures and algorithms
Show steps
Solidify your understanding of data structures and algorithms by solving coding problems.
Show steps
Show steps
Show steps
- Start with easier problems and gradually increase the difficulty.
- Focus on understanding the problem statement and coming up with an efficient solution.
- Implement your solution in a coding language of your choice and test it thoroughly.
- Review your solution and identify areas for improvement.
Identify and connect with experienced professionals in the field
Show steps
Expand your network and gain guidance from those already working in the data analytics industry.
Show steps
Show steps
Show steps
- Attend industry events and conferences
- Reach out to your alumni network and professional organizations
- Request informational interviews with individuals who work in roles you are interested in
Attend Coursera's 'Introduction to Data Analysis with R'
Show steps
Gain a comprehensive understanding of data analysis techniques by completing this Coursera course.
Show steps
Show steps
Show steps
- Enroll in the course and complete the video lectures
- Follow along with the hands-on exercises and assignments
- Participate in the discussion forums to interact with peers and ask questions
Build a data visualization dashboard using Tableau or Power BI
Show steps
Develop your data visualization skills by creating a dashboard that communicates insights from a dataset.
Show steps
Show steps
Show steps
- Choose a dataset that you are interested in
- Identify the key insights that you want to communicate with your dashboard
- Select appropriate charts and graphs to represent the data
- Build and iterate on your dashboard until you are satisfied with the results
Participate in a Kaggle competition related to data analytics
Show steps
Challenge yourself and apply your skills by participating in a data analytics competition.
Show steps
Show steps
Show steps
- Identify a Kaggle competition that aligns with your interests
- Form a team or work individually on the competition
- Develop and implement a data analytics solution
- Submit your solution and track your progress on the leaderboard
Career center
Learners who complete Building the Data Academy will develop knowledge and skills
that may be useful to these careers:
Data Science Instructor
Data Science Instructor
Data Science Instructors teach data science concepts and techniques. They work with students to develop data science skills and knowledge. This course may be useful for Data Science Instructors as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful for Data Scientists as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models. They work with data scientists to identify and solve machine learning problems. This course may be useful for Machine Learning Engineers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Architect
Data Architect
Data Architects design and build data management systems. They work with business stakeholders to identify data needs and develop data management strategies. This course may be useful for Data Architects as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations and inform decision-making. This course may be useful for Data Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Consultant
Consultant
Consultants provide advice and guidance to organizations. They work with clients to identify problems, develop solutions, and implement changes. This course may be useful for Consultants as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Engineer
Data Engineer
Data Engineers build and maintain data pipelines. They work with data scientists and data analysts to ensure that data is available and accessible for analysis. This course may be useful for Data Engineers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to identify trends and opportunities. They work with business stakeholders to develop and implement data-driven strategies. This course may be useful for Business Intelligence Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Governance Specialist
Data Governance Specialist
Data Governance Specialists develop and implement data governance policies and procedures. They work with business stakeholders and IT staff to ensure that data is used ethically and responsibly. This course may be useful for Data Governance Specialists as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Program Manager
Program Manager
Program Managers oversee multiple projects. They work with stakeholders to define program goals, develop program plans, and track program progress. This course may be useful for Program Managers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Security Analyst
Data Security Analyst
Data Security Analysts protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. They work with business stakeholders and IT staff to implement data security measures. This course may be useful for Data Security Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Privacy Analyst
Data Privacy Analyst
Data Privacy Analysts assess and mitigate data privacy risks. They work with business stakeholders and IT staff to ensure that data is collected, used, and stored in compliance with privacy regulations. This course may be useful for Data Privacy Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Analytics Manager
Data Analytics Manager
Data Analytics Managers plan and execute data analytics initiatives within an organization. They work with business stakeholders to identify data needs, develop data analytics strategies, and implement data analytics solutions. This course may be useful for Data Analytics Managers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Project Manager
Project Manager
Project Managers plan and execute projects. They work with stakeholders to define project scope, develop project plans, and track project progress. This course may be useful for Project Managers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
Data Evangelist
Data Evangelist
Data Evangelists promote the use of data within an organization. They work with stakeholders to identify data opportunities, develop data strategies, and implement data-driven solutions. This course may be useful for Data Evangelists as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.
For more career information including salaries, visit:
OpenCourser.com/course/5zudjb/building
Reading list
We've selected 16 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
Building the Data Academy.
Save
Comprehensive guide to deep learning, one of the most popular and powerful machine learning techniques. It covers the basics of deep learning, as well as some of the most advanced techniques used in the field.
Practical guide to deep learning, one of the most popular and powerful machine learning techniques. It covers the basics of deep learning, as well as some of the most advanced techniques used in the field.
Practical guide to data science, using Python as the programming language. It covers the basics of data science, as well as some of the most advanced techniques used in the field.
Practical guide to using Pandas, a popular Python library for data analysis. It covers the basics of Pandas, as well as some of the most advanced techniques used in the field.
Practical guide to using data science to solve business problems. It covers topics such as data mining, machine learning, and predictive analytics.
Save
Comprehensive guide to data mining, a process of extracting knowledge from data. It covers the basics of data mining, as well as some of the most advanced techniques used in the field.
Provides a comprehensive overview of data science, a field that combines statistics, computer science, and domain knowledge to extract knowledge from data. It covers the basics of data science, as well as some of the most advanced techniques used in the field.
Provides a comprehensive overview of machine learning, covering different algorithms and techniques. It good reference for students who want to learn more about the different tools and techniques used in machine learning.
Provides a practical introduction to data analysis using Python. It focuses on using Python's data analysis libraries, such as NumPy and Pandas.
Practical guide to using data analytics to solve problems in the social sciences. It covers the basics of data analytics, as well as some of the most advanced techniques used in the field.
Provides a comprehensive overview of data analytics, making it a great starting point for those new to the field. It covers the basics of data collection, analysis, and visualization.
Provides a comprehensive overview of statistical methods used in data analysis. It covers the basics of statistics, as well as some of the most advanced techniques used in the field.
Save
Practical guide to data visualization, a process of representing data in a visual format. It covers the basics of data visualization, as well as some of the most advanced techniques used in the field.
Provides a gentle introduction to machine learning, making it accessible to those with no prior experience. It covers the basics of supervised and unsupervised learning, as well as some of the most popular machine learning algorithms.
Introduces deep learning, a subset of machine learning that is particularly useful for analyzing large and complex data sets. It provides a good overview of the fundamental concepts and techniques.
A practical guide to using R for data analytics, covering data manipulation, analysis, and visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5zudjb/building
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Time
22 hours
Level
Introductory
Via
Pluralsight
Instructor
Pluralsight LIVE
Language
English
Good to know
Addresses growing demand from organizations for employees who are data analytics literate
In-house training helps organizations prepare for AI and automation changes
Provides tips for designing effective training programs
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