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In this course, you will learn how AnyCompany Media, a global giant in the media and entertainment industry, overcomes their data challenges. Follow their journey to become a data driven organization in their operations and strategic decision-making. Throughout the course, you will learn about the fundamental concepts of analytics, high level overview of machine learning, the 5 Vs of big data, and AWS services for specific analytics use cases.

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In this course, you will learn how AnyCompany Media, a global giant in the media and entertainment industry, overcomes their data challenges. Follow their journey to become a data driven organization in their operations and strategic decision-making. Throughout the course, you will learn about the fundamental concepts of analytics, high level overview of machine learning, the 5 Vs of big data, and AWS services for specific analytics use cases.

You will then learn how AnyCompany Media, a global giant in the media and entertainment industry, overcomes its data and analytics challenges. Follow along as it becomes data-driven in operations and strategic decision-making with data lakes, data warehouses, and modern data architecture on Amazon Web Services (AWS).

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What's inside

Syllabus

Fundamentals of Analytics on AWS – Part 1

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops analytics techniques and strategies, which are core principles of business and industry
Emphasizes hands-on learning, ensuring practical application of concepts
Introduces learners to the latest tools and technologies in data analytics
Provides a comprehensive overview of data science concepts, making it accessible to beginners
Involves working on real-world case studies, fostering problem-solving abilities
Teaches how to implement data science techniques in various industries

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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 Fundamentals of Analytics on AWS with these activities:
Organize Course Content
Establish a structured system for managing course materials, notes, and resources, promoting organization and efficient learning.
Show steps
  • Create a digital or physical notebook to store all course-related content.
  • Categorize and label notes, assignments, and other resources.
  • Use color-coding or other visual cues to differentiate important concepts.
  • Regularly review and refine your organizational system.
Seek Guidance from Experts
Connect with professionals in the analytics field to gain insights, expand your network, and receive support throughout your learning journey.
Show steps
  • Identify potential mentors through LinkedIn or industry events.
  • Reach out and introduce yourself, expressing your interest in their guidance.
  • Schedule regular meetings or calls to discuss your progress and seek advice.
Review Analytics Concepts
Familiarize yourself with the core principles of analytics to lay a solid foundation for the course.
Browse courses on Data Analytics
Show steps
  • Read introductory articles or textbooks on analytics fundamentals.
  • Attend a webinar or online course on the topic.
  • Review case studies or examples of successful analytics implementations.
Three other activities
Expand to see all activities and additional details
Show all six activities
Enhance Machine Learning Skills
Refine your machine learning abilities to enhance your understanding and application of advanced analytics techniques.
Show steps
  • Review foundational machine learning concepts.
  • Practice implementing machine learning algorithms using Python or R.
  • Participate in online coding challenges or competitions.
  • Attend workshops or webinars on machine learning.
Explore AWS Analytics Services
Gain practical experience with the various AWS services used for analytics, enhancing your understanding of their capabilities.
Show steps
  • Follow tutorials on AWS services such as Amazon S3, Redshift, and Athena.
  • Create a free AWS account and experiment with these services.
  • Join online forums or communities to connect with AWS experts and learners.
Collaborate on Analytics Projects
Engage with peers to tackle real-world analytics challenges, fostering teamwork and enhancing your applied skills.
Browse courses on Machine Learning Projects
Show steps
  • Form study groups with fellow learners.
  • Choose a dataset or case study for analysis.
  • Collaborate on data exploration, modeling, and visualization.
  • Present your findings and discuss insights with the group.

Career center

Learners who complete Fundamentals of Analytics on AWS will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts collect, clean, and analyze data to help organizations understand trends and make better decisions. They use a variety of analytical techniques to identify patterns and insights in data. The Fundamentals of Analytics on AWS course can help aspiring Data Analysts develop the skills and knowledge needed to succeed in this role. The course covers topics such as data collection, data cleaning, data analysis, and data visualization. It also provides an overview of AWS services for analytics, which can be valuable for Data Analysts who want to work with AWS.
Data Scientist
Data Scientists use machine learning and other advanced analytical techniques to extract insights from data. They work in a variety of industries, including finance, healthcare, and retail. The Fundamentals of Analytics on AWS course can help aspiring Data Scientists develop the foundational skills and knowledge needed to succeed in this role. The course covers topics such as machine learning, big data, and AWS services for analytics.
Data Engineer
Data Engineers design, build, and maintain data systems. They work with data architects to ensure that data is stored, processed, and accessed効率的に. The Fundamentals of Analytics on AWS course can help aspiring Data Engineers develop the skills and knowledge needed to succeed in this role. The course covers topics such as data architecture, data engineering, and AWS services for data engineering.
Business Analyst
Business Analysts use data to help businesses understand their customers, markets, and operations. They use a variety of analytical techniques to identify opportunities and solve problems. The Fundamentals of Analytics on AWS course can help aspiring Business Analysts develop the skills and knowledge needed to succeed in this role. The course covers topics such as data analysis, data visualization, and business intelligence.
Analytics Manager
Analytics Managers lead teams of data analysts and data scientists. They are responsible for developing and implementing data analytics strategies. The Fundamentals of Analytics on AWS course can help aspiring Analytics Managers develop the skills and knowledge needed to succeed in this role. The course covers topics such as data analytics, data management, and AWS services for analytics.
Data Architect
Data Architects design and build data systems. They work with data engineers to ensure that data is stored, processed, and accessed efficiently. The Fundamentals of Analytics on AWS course can help aspiring Data Architects develop the skills and knowledge needed to succeed in this role. The course covers topics such as data architecture, data modeling, and AWS services for data architecture.
Data Visualization Specialist
Data Visualization Specialists create visual representations of data. They use a variety of tools and techniques to make data more accessible and understandable. The Fundamentals of Analytics on AWS course can help aspiring Data Visualization Specialists develop the skills and knowledge needed to succeed in this role. The course covers topics such as data visualization, data storytelling, and AWS services for data visualization.
Big Data Engineer
Big Data Engineers work with large and complex data sets. They use a variety of tools and technologies to store, process, and analyze big data. The Fundamentals of Analytics on AWS course can help aspiring Big Data Engineers develop the skills and knowledge needed to succeed in this role. The course covers topics such as big data, data engineering, and AWS services for big data.
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy machine learning models. They work with data scientists to ensure that machine learning models are accurate and efficient. The Fundamentals of Analytics on AWS course can help aspiring Machine Learning Engineers develop the skills and knowledge needed to succeed in this role. The course covers topics such as machine learning, machine learning engineering, and AWS services for machine learning.
Cloud Architect
Cloud Architects design and build cloud-based solutions. They work with clients to understand their business needs and design solutions that meet those needs. The Fundamentals of Analytics on AWS course can help aspiring Cloud Architects develop the skills and knowledge needed to succeed in this role. The course covers topics such as cloud computing, cloud architecture, and AWS services for cloud computing.
Systems Engineer
Systems Engineers design, build, and maintain complex systems. They work with a variety of hardware and software components to create systems that meet the needs of users. The Fundamentals of Analytics on AWS course can help aspiring Systems Engineers develop the skills and knowledge needed to succeed in this role. The course covers topics such as systems engineering, systems architecture, and AWS services for systems engineering.
Software Engineer
Software Engineers design, build, and maintain software applications. They work with a variety of programming languages and technologies to create software that meets the needs of users. The Fundamentals of Analytics on AWS course can help aspiring Software Engineers develop the skills and knowledge needed to succeed in this role. The course covers topics such as software engineering, software development, and AWS services for software development.
Network Engineer
Network Engineers design, build, and maintain computer networks. They work with a variety of networking technologies to create networks that meet the needs of users. The Fundamentals of Analytics on AWS course can help aspiring Network Engineers develop the skills and knowledge needed to succeed in this role. The course covers topics such as networking, network engineering, and AWS services for networking.
Security Engineer
Security Engineers design, build, and maintain security systems. They work with a variety of security technologies to create systems that protect data and systems from unauthorized access. The Fundamentals of Analytics on AWS course can help aspiring Security Engineers develop the skills and knowledge needed to succeed in this role. The course covers topics such as security, security engineering, and AWS services for security.
Database Administrator
Database Administrators design, build, and maintain databases. They work with a variety of database technologies to create databases that meet the needs of users. The Fundamentals of Analytics on AWS course can help aspiring Database Administrators develop the skills and knowledge needed to succeed in this role. The course covers topics such as database administration, database management, and AWS services for database administration.

Reading list

We've selected seven 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 Fundamentals of Analytics on AWS.
Provides a practical introduction to data analysis with Pandas, a popular Python library for data manipulation and analysis. It covers essential Pandas concepts and techniques, as well as real-world examples to help you apply your learning.
Provides a comprehensive overview of reinforcement learning concepts and techniques. It covers topics such as Markov decision processes, value functions, and reinforcement learning algorithms.
Provides a comprehensive overview of computer vision algorithms and techniques. It covers topics such as image processing, object detection, and image classification.
Provides a comprehensive overview of data analytics concepts and techniques, making it a great starting point for beginners. It covers topics such as data collection, cleaning, analysis, and visualization, and includes hands-on exercises to reinforce learning.
Provides a comprehensive overview of data mining techniques, including data preprocessing, feature selection, model evaluation, and data visualization. It also discusses the applications of data mining in various domains.
Provides a practical introduction to deep learning using Python and the Keras library. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a gentle introduction to machine learning concepts and techniques, using Python as the programming language. It covers topics such as supervised and unsupervised learning, model evaluation, and feature engineering.

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