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Mohamed Sarwat
Systems that perform big data analytics require highly distributed architectures and new levels of memory and processing power. This course covers main topics associated with systems such as Hadopp MapReduce, Apache Spark, and Graph Processing Engines.
Register for this course and see more details by visiting:
OpenCourser.com/course/0ls0tz/big
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers fundamental concepts in big data analytics, which is a high-demand field in the tech industry
Emphasizes practical skills in working with big data tools like Hadoop MapReduce and Apache Spark
Provides a comprehensive overview of graph processing, which is a rapidly growing area in data science
Suitable for students interested in careers in data engineering, data science, or machine learning
Taught by experienced industry professionals, Mohamed Sarwat, who bring real-world insights to the classroom
Requires students to have some prior programming experience, particularly in Python
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Save Big Data Tools 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 Big Data Tools with these
activities:
Review the Syllabus and Course Materials
Show steps
Reviewing the syllabus and course literature will help you align your expectations with the course structure and pace.
Show steps
-
Review the syllabus and take notes about important dates and topics.
-
Obtain all required textbooks and reading materials.
-
Create a dedicated folder to store and organize course materials.
Follow Online Tutorials on Hadoop and Spark
Show steps
Following tutorials on Hadoop and Spark will provide you with hands-on experience and deepen your understanding of these technologies.
Browse courses on
Hadoop
Show steps
-
Identify relevant tutorials that cover Hadoop MapReduce and Apache Spark.
-
Follow the tutorials step-by-step and complete the exercises.
-
Make notes and document any difficulties encountered.
Solve Hadoop MapReduce Practice Problems
Show steps
Solving practice problems will enhance your problem-solving skills and solidify your understanding of Hadoop MapReduce.
Browse courses on
Hadoop MapReduce
Show steps
-
Gather a collection of Hadoop MapReduce practice problems.
-
Attempt to solve the problems on your own.
-
Check your solutions against provided answers or consult online forums for assistance.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Study Group or Online Forum
Show steps
Engaging in discussion with peers will provide you with diverse perspectives and enhance your understanding of the course material.
Show steps
-
Identify and join an online forum or study group related to the course.
-
Actively participate in discussions and ask questions.
-
Share your knowledge and insights with others.
Build a Mini Hadoop Cluster
Show steps
Setting up a mini Hadoop cluster will provide you with practical experience in configuring and managing a distributed computing environment.
Browse courses on
Hadoop
Show steps
-
Gather the necessary hardware and software resources.
-
Install and configure Hadoop on each node of the cluster.
-
Test the cluster by running a simple Hadoop job.
Mentor a Junior Student or Colleague
Show steps
Mentoring others will reinforce your understanding of the course material and develop your communication skills.
Browse courses on
Mentorship
Show steps
-
Identify a junior student or colleague who is interested in learning about big data analytics.
-
Provide guidance and support on topics related to the course.
-
Encourage them to ask questions and share their progress.
Contribute to an Open-Source Big Data Project
Show steps
Contributing to an open-source project will expose you to real-world big data applications and development practices.
Browse courses on
Open Source
Show steps
-
Identify an open-source big data project that aligns with your interests.
-
Familiarize yourself with the project's codebase and documentation.
-
Make a small contribution, such as fixing a bug or adding a feature.
Review the Syllabus and Course Materials
Show steps
Reviewing the syllabus and course literature will help you align your expectations with the course structure and pace.
Show steps
Show steps
Show steps
- Review the syllabus and take notes about important dates and topics.
- Obtain all required textbooks and reading materials.
- Create a dedicated folder to store and organize course materials.
Follow Online Tutorials on Hadoop and Spark
Show steps
Following tutorials on Hadoop and Spark will provide you with hands-on experience and deepen your understanding of these technologies.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Identify relevant tutorials that cover Hadoop MapReduce and Apache Spark.
- Follow the tutorials step-by-step and complete the exercises.
- Make notes and document any difficulties encountered.
Solve Hadoop MapReduce Practice Problems
Show steps
Solving practice problems will enhance your problem-solving skills and solidify your understanding of Hadoop MapReduce.
Browse courses on
Hadoop MapReduce
Show steps
Show steps
Show steps
- Gather a collection of Hadoop MapReduce practice problems.
- Attempt to solve the problems on your own.
- Check your solutions against provided answers or consult online forums for assistance.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Study Group or Online Forum
Show steps
Engaging in discussion with peers will provide you with diverse perspectives and enhance your understanding of the course material.
Show steps
Show steps
Show steps
- Identify and join an online forum or study group related to the course.
- Actively participate in discussions and ask questions.
- Share your knowledge and insights with others.
Build a Mini Hadoop Cluster
Show steps
Setting up a mini Hadoop cluster will provide you with practical experience in configuring and managing a distributed computing environment.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Gather the necessary hardware and software resources.
- Install and configure Hadoop on each node of the cluster.
- Test the cluster by running a simple Hadoop job.
Mentor a Junior Student or Colleague
Show steps
Mentoring others will reinforce your understanding of the course material and develop your communication skills.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify a junior student or colleague who is interested in learning about big data analytics.
- Provide guidance and support on topics related to the course.
- Encourage them to ask questions and share their progress.
Contribute to an Open-Source Big Data Project
Show steps
Contributing to an open-source project will expose you to real-world big data applications and development practices.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify an open-source big data project that aligns with your interests.
- Familiarize yourself with the project's codebase and documentation.
- Make a small contribution, such as fixing a bug or adding a feature.
Career center
Learners who complete Big Data Tools will develop knowledge and skills
that may be useful to these careers:
Big Data Analyst
Big Data Analyst
Big Data Analysts use big data tools and technologies to analyze data and extract insights from it. This course can help you develop the skills you need to become a successful Big Data Analyst by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Big Data Analysts because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases, including big data databases. This course can help you develop the skills you need to become a successful Database Administrator by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Database Administrators because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Data Engineer
Data Engineer
Data Engineers use a variety of big data tools and technologies to build and maintain data pipelines that are used to collect, process, and store data. This course can help you develop the skills you need to become a successful Data Engineer by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Data Engineers because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Data Architect
Data Architect
Data Architects are responsible for designing and managing data systems, including big data systems. This course can help you develop the skills you need to become a successful Data Architect by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Data Architects because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Data Scientist
Data Scientist
Data Scientists use big data tools and technologies to analyze data and extract insights from it. This course can help you develop the skills you need to become a successful Data Scientist by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Data Scientists because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems, including big data software systems. This course can help you develop the skills you need to become a successful Software Engineer by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Software Engineers because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Computer Scientist
Computer Scientist
Computer Scientists research and develop new computing technologies, including big data technologies. This course can help you develop the skills you need to become a successful Computer Scientist by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Computer Scientists because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Data Quality Analyst
Data Quality Analyst
Data Quality Analysts ensure that data is accurate and reliable. This course can help you develop the skills you need to become a successful Data Quality Analyst by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Data Quality Analysts because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Information Systems Manager
Information Systems Manager
Information Systems Managers plan, implement, and manage information systems, including big data systems. This course can help you develop the skills you need to become a successful Information Systems Manager by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Information Systems Managers because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Business Analyst
Business Analyst
Business Analysts use data to help businesses make better decisions. This course can help you develop the skills you need to become a successful Business Analyst by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Business Analysts because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to help businesses make better decisions. This course can help you develop the skills you need to become a successful Operations Research Analyst by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Operations Research Analysts because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Statistician
Statistician
Statisticians use data to make informed decisions. This course can help you develop the skills you need to become a successful Statistician by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Statisticians because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Financial Analyst
Financial Analyst
Financial Analysts use data to help businesses make better financial decisions. This course can help you develop the skills you need to become a successful Financial Analyst by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Financial Analysts because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to help businesses make better marketing decisions. This course can help you develop the skills you need to become a successful Marketing Analyst by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Marketing Analysts because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
Risk Analyst
Risk Analyst
Risk Analysts use data to help businesses identify and manage risks. This course can help you develop the skills you need to become a successful Risk Analyst by providing you with a foundation in the core concepts of big data analytics, as well as experience working with some of the most popular big data tools. This course is particularly relevant to Risk Analysts because it provides hands-on experience with Hadoop MapReduce and Apache Spark, which are two of the most widely used big data tools.
For more career information including salaries, visit:
OpenCourser.com/course/0ls0tz/big
Reading list
We've selected ten 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
Big Data Tools.
Comprehensive guide to Apache Spark, including its programming model, APIs, and use cases. Essential reading for Spark developers.
In-depth coverage of Hadoop, including its architecture, components, and applications. Useful as a reference guide.
Covers python-based techniques for big data analysis, including data wrangling, visualization, and machine learning.
Covers practical techniques for building big data applications using Java and Hadoop. Provides hands-on examples.
Save
Covers the intersection of big data analytics and machine learning, providing practical insights and examples.
Provides a practical guide to big data analytics, covering data collection, processing, analysis, and visualization.
Save
Covers R-based techniques for big data analysis, including data manipulation, visualization, and statistical modeling.
Provides a theoretical foundation for graph processing engines and algorithms. Useful for understanding the underlying concepts.
Save
Provides a comprehensive overview of data mining techniques, including clustering, classification, and association rule mining.
Provides a simplified and approachable introduction to big data analytics concepts and technologies.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0ls0tz/big
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Time
14 hours
Via
Coursera
Institution
Arizona State University
Instructor
Mohamed Sarwat
This course belongs to a
collection
called
Data Systems. It's comprised of five courses:
- NoSQL Database Systems
- Distributed Database Systems
- Data Management in the Cloud
- Core Database Concepts
- Big Data Tools (viewing)
Good to know
Covers fundamental concepts in big data analytics, which is a high-demand field in the tech industry
Emphasizes practical skills in working with big data tools like Hadoop MapReduce and Apache Spark
Provides a comprehensive overview of graph processing, which is a rapidly growing area in data science
Suitable for students interested in careers in data engineering, data science, or machine learning
Taught by experienced industry professionals, Mohamed Sarwat, who bring real-world insights to the classroom
Requires students to have some prior programming experience, particularly in Python
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