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Samant Bali
and
Kenny Mobley
This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.
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OpenCourser.com/course/3z826x/data
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What's inside
Syllabus
Introduction
This Azure training course is designed to equip the students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as R, and Apache Spark.
Read more
Syllabus
Introduction
This Azure training course is designed to equip the students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as R, and Apache Spark.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Teaches essential analytical tools such as Python, R, and Apache Spark
Helps students understand the importance of big data and big data analytics for business decision-making
Develops skills for processing, storing, and analyzing big data
Provides hands-on labs and interactive materials for better learning
Improves students' mathematical and programming skills
Is taught by Kenny Mobley and Samant Bali, who are experienced in data analytics
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Reviews summary
Practical azure data processing essentials
According to learners, this course offers a practical and comprehensive overview of Azure data processing. Students frequently highlight the hands-on labs and clear demonstrations as particularly effective, providing a strong foundation for applying concepts in real-world scenarios. While widely praised for its relevant content for professionals, some note that the pace can be fast and it often assumes prior knowledge in areas like SQL or basic programming, suggesting it's best for those with some existing technical background rather than absolute beginners.
Instructor provides concise explanations and easy-to-follow demonstrations.
"The instructor's explanations were concise and to the point."
"The demos were clear and easy to follow, making the transition to my own projects smoother."
"The instructor did a fantastic job breaking down complex Azure concepts into manageable parts."
Covers current industry needs with relevant Azure data processing services.
"Solid overview of data processing on Azure. The sections on Databricks and Polybase were very useful."
"This course delivered exactly what it promised – a practical guide to processing data with Azure."
"The course content is highly relevant to current industry needs. I appreciated the focus on real-time analytics with Stream Analytics."
"Very comprehensive and practical! The instructor did a fantastic job breaking down complex Azure concepts into manageable parts."
Provides practical, applied understanding of Azure data services.
"The hands-on labs were incredibly helpful and demystified complex topics like Azure Data Factory pipelines and Stream Analytics."
"This course delivered exactly what it promised – a practical guide... The demos were clear and easy to follow, making the transition to my own projects smoother."
"Hands down one of the best courses for Azure data engineering. The practical exercises solidified my understanding of Data Factory and Stream Analytics."
"I particularly valued the focus on real-world applications and pipeline creation. I feel much more confident applying these concepts in my work."
Less focus on improving programming or mathematical skills than implied.
"The 'mathematical and programming skills' improvement promised in the description isn't really a focus here; it's more about using Azure tools."
Occasional minor issues with lab replication or version differences noted.
"troubleshooting errors in labs was difficult."
"some of the demos were hard to replicate due to minor version differences or unclear instructions."
Presents challenges for beginners due to its fast pace and assumed knowledge.
"I found the pace a bit fast in some modules, and a strong prior understanding of SQL and basic Python/R is definitely recommended to keep up."
"I struggled with the pace and lack of deeper explanations for certain concepts. It felt like it assumed a lot of prior knowledge, especially for those new to cloud data platforms."
"Some material felt a little rushed, and I had to supplement with external documentation for full understanding."
"The course rushes through too many topics without sufficient depth. As someone with some experience, I found myself skipping parts, but a beginner would be completely lost."
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 Data Processing with Azure with these
activities:
Read 'Big Data Analytics' by Michael Minelli
Show steps
Read a book on big data analytics to gain insights and understanding of the subject matter.
View
Big Data, Big Analytics: Emerging Business...
on Amazon
Show steps
-
Read one chapter per week
-
Take notes and highlight important concepts
-
Discuss the book with classmates or online forums
Review Python programming
Show steps
Prepare for this course by reviewing python programming. This will provide a solid foundation for understanding the materials.
Browse courses on
Python Programming
Show steps
-
Read online tutorials about python programming basics
-
Complete practice problems using an online programming judge
-
Work through a python programming tutorial or book
Review linear algebra concepts
Show steps
Refresh your knowledge of linear algebra concepts used in this course, such as matrix operations and vector spaces.
Browse courses on
Linear Algebra
Show steps
-
Review notes or textbooks from a previous linear algebra course
-
Solve practice problems involving linear algebra concepts
-
Complete online quizzes or assessments on linear algebra
Five other activities
Expand to see all activities and additional details
Show all eight activities
Organize your course materials
Show steps
Keep your course materials organized to enhance your understanding of the content.
Show steps
-
Create a system for organizing your notes, assignments, and other materials
-
Regularly review and update your organized materials
-
Consider using digital tools or apps to assist in organizing your materials
Complete Azure Databricks practice problems
Show steps
Enhance your understanding of Azure Databricks by completing practice problems.
Browse courses on
Azure Databricks
Show steps
-
Find online resources or tutorials that provide practice problems for Azure Databricks
-
Set aside time to regularly work through these practice problems
-
Review your solutions and identify areas for improvement
Join a study group with classmates
Show steps
Study with classmates regularly to discuss course materials, ask questions, and share insights.
Show steps
-
Find a group of classmates to study with
-
Meet regularly to discuss course materials
-
Collaborate on assignments and projects
Create a small data analysis project
Show steps
Develop a small project to solidify your understanding of data analysis techniques.
Show steps
-
Identify a small dataset to analyze
-
Use data analysis tools and techniques to explore and analyze the data
-
Summarize your findings and insights in a brief report or presentation
Participate in a data science or analytics competition
Show steps
Test your skills and knowledge in a competitive environment.
Show steps
-
Identify a relevant data science or analytics competition
-
Form a team or participate individually
-
Work on the competition and submit your solution
Read 'Big Data Analytics' by Michael Minelli
Show steps
Read a book on big data analytics to gain insights and understanding of the subject matter.
View
Big Data, Big Analytics: Emerging Business...
on Amazon
Show steps
Show steps
Show steps
- Read one chapter per week
- Take notes and highlight important concepts
- Discuss the book with classmates or online forums
Review Python programming
Show steps
Prepare for this course by reviewing python programming. This will provide a solid foundation for understanding the materials.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Read online tutorials about python programming basics
- Complete practice problems using an online programming judge
- Work through a python programming tutorial or book
Review linear algebra concepts
Show steps
Refresh your knowledge of linear algebra concepts used in this course, such as matrix operations and vector spaces.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review notes or textbooks from a previous linear algebra course
- Solve practice problems involving linear algebra concepts
- Complete online quizzes or assessments on linear algebra
Five other activities
Expand to see all activities and additional details
Show all eight activities
Organize your course materials
Show steps
Keep your course materials organized to enhance your understanding of the content.
Show steps
Show steps
Show steps
- Create a system for organizing your notes, assignments, and other materials
- Regularly review and update your organized materials
- Consider using digital tools or apps to assist in organizing your materials
Complete Azure Databricks practice problems
Show steps
Enhance your understanding of Azure Databricks by completing practice problems.
Browse courses on
Azure Databricks
Show steps
Show steps
Show steps
- Find online resources or tutorials that provide practice problems for Azure Databricks
- Set aside time to regularly work through these practice problems
- Review your solutions and identify areas for improvement
Join a study group with classmates
Show steps
Study with classmates regularly to discuss course materials, ask questions, and share insights.
Show steps
Show steps
Show steps
- Find a group of classmates to study with
- Meet regularly to discuss course materials
- Collaborate on assignments and projects
Create a small data analysis project
Show steps
Develop a small project to solidify your understanding of data analysis techniques.
Show steps
Show steps
Show steps
- Identify a small dataset to analyze
- Use data analysis tools and techniques to explore and analyze the data
- Summarize your findings and insights in a brief report or presentation
Participate in a data science or analytics competition
Show steps
Test your skills and knowledge in a competitive environment.
Show steps
Show steps
Show steps
- Identify a relevant data science or analytics competition
- Form a team or participate individually
- Work on the competition and submit your solution
Career center
Learners who complete Data Processing with Azure will develop knowledge and skills
that may be useful to these careers:
Chief Data Officer
Chief Data Officer
Chief Data Officers are responsible for overseeing all aspects of data management within an organization. They work with senior leadership to set the strategic direction for data initiatives and ensure that data is used effectively to support business goals. This course may be useful for aspiring Chief Data Officers because it provides a comprehensive overview of data processing, storage, analysis, and governance.
Data Scientist Manager
Data Scientist Manager
Data Scientist Managers lead teams of Data Scientists and other data professionals. They are responsible for setting the strategic direction for data science projects and ensuring that projects are completed on time and within budget. This course may be useful for aspiring Data Scientist Managers because it provides a foundation in data processing, analysis, and management.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts are responsible for developing and implementing data governance policies and procedures. They work with a variety of stakeholders, including data owners, data stewards, and data users, to ensure that data is used ethically and responsibly. This course may be useful for aspiring Data Governance Analysts because it provides a foundation in data processing, storage, and security.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy machine learning models. They work with a variety of data sources and tools, and they may specialize in a particular area, such as natural language processing or computer vision. This course may be useful for aspiring Machine Learning Engineers because it provides a foundation in data processing, analysis, and visualization.
Data Science Consultant
Data Science Consultant
Data Science Consultants help businesses use data to make better decisions. They work with a variety of clients, including Fortune 500 companies and startups, to implement data science solutions. This course may be useful for aspiring Data Science Consultants because it provides a foundation in data processing, analysis, and visualization.
Data Scientist
Data Scientist
Data Scientists use data to build predictive models and solve business problems. They work with a variety of data sources and tools, and they may specialize in a particular area, such as machine learning or artificial intelligence. This course may be useful for aspiring Data Scientists because it provides a foundation in data processing, analysis, and visualization.
Data Architect
Data Architect
Data Architects design and build data architectures that meet the needs of businesses. They work with a variety of data sources and technologies, and they may specialize in a particular area, such as data warehousing or big data. This course may be useful for aspiring Data Architects because it provides a foundation in data processing, storage, and analysis.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. They work with a variety of data sources and tools, and they may specialize in a particular area, such as natural language processing or computer vision. This course may be useful for aspiring Machine Learning Researchers because it provides a foundation in data processing, analysis, and visualization.
Business Analyst
Business Analyst
Business Analysts help businesses improve their operations and make better decisions by analyzing data. They work with a variety of data sources and tools, and they may specialize in a particular area, such as financial analysis or marketing research. This course may be useful for aspiring Business Analysts because it provides a foundation in data processing, analysis, and visualization.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines that collect, transform, and store data for analysis. They work closely with Data Scientists and other data professionals to ensure that data is available in a timely and reliable manner. This course may be useful for aspiring Data Engineers because it provides a foundation in data processing, storage, and analysis.
Database Administrator
Database Administrator
Database Administrators maintain and optimize databases to ensure that they are available and reliable. They work with a variety of database technologies, and they may specialize in a particular area, such as performance tuning or security. This course may be useful for aspiring Database Administrators because it provides a foundation in data storage, management, and security.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to help businesses make informed decisions. They use a variety of statistical methods to draw conclusions from data, and they may specialize in a particular area, such as survey research or quality control. This course may be useful for aspiring Statisticians because it provides a foundation in data processing, analysis, and visualization.
Product Manager
Product Manager
Product Managers are responsible for developing and launching new products and features. They work with a variety of stakeholders, including engineers, designers, and marketers, to ensure that products meet the needs of customers. This course may be useful for aspiring Product Managers because it provides a foundation in data processing, analysis, and visualization.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. They use a variety of tools and techniques to extract insights from data, and they may specialize in a particular area, such as financial analysis or marketing research. This course may be useful for aspiring Data Analysts because it provides a foundation in data processing, analysis, and visualization.
Software Engineer
Software Engineer
Software Engineers design, build, and maintain software applications. They work with a variety of programming languages and technologies, and they may specialize in a particular area, such as web development or mobile development. This course may be useful for aspiring Software Engineers because it provides a foundation in data processing, storage, and analysis.
For more career information including salaries, visit:
OpenCourser.com/course/3z826x/data
Reading list
We've selected nine 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
Data Processing with Azure.
This cookbook provides practical recipes and solutions for common problems encountered in data integration and transformation with Azure Data Factory. It valuable resource for those who want to learn how to use Azure Data Factory effectively and efficiently.
Provides an introduction to Python for data analysis and covers the fundamentals of data science, including data cleaning, data exploration, and data visualization using Python libraries such as NumPy, Pandas, and Matplotlib.
Save
Teaches you how to use the R programming language for data science, including data analysis, graphics, and machine learning.
Provides an introduction to data science with practical examples and provides the information you need to understand and use the key concepts, methods, and tools of data science.
Provides practical techniques for working with very large datasets, and includes notes on optimization and performance and a detailed case study on natural language processing.
Offers a friendly and accessible guide to machine learning, featuring simple explanations and a wealth of real-world examples.
Provides a comprehensive and accessible guide to the terms and concepts used in the field of big data, making it a useful reference tool for those new to the subject.
Helps you appreciate the challenge of managing and processing data in large distributed systems and provides actionable guidance on designing, building, and running Hadoop clusters.
Teaches you how to use SQL Server Data Tools to develop and deploy complete business intelligence solutions.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3z826x/data
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Effort
3 weeks of study, 4-8 hours per week
Level
Intermediate
Via
Coursera
Institution
LearnQuest
Instructors
Samant Bali
Kenny Mobley
Language
English
Transcripts
Español
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Português
Deutsch
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