We may earn an affiliate commission when you visit our partners.
Pluralsight LIVE

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.

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.

Enroll now

What's inside

Syllabus

Building the Data Academy

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:
Save

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'
Gain valuable insights into how data science can be applied to solve business problems.
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
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
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
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
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
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'
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
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
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

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 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 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 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 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 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
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 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 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 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 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 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 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 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 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 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.

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.
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.
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.
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.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Building the Data Academy.
AML Case Investigation Skills
Introduction to Health Technology Assessment
Approaches to Data Enabled Decision Making
Meta Marketing Science Certification Exam
Predictive Analytics for Business Planning: Time-Series...
Politics and Ethics of Data Analytics in the Public Sector
Data Lake Mastery: The Key to Big Data & Data Engineering
Data Literacy Foundations
Sports Management: Data and Analytics
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser