Hands-On Introduction to Real-Time Analytics
Learn how to consume and analyze data streams from anywhere and derive actionable results instantly.
Upcoming Session
Aug 24 – 25
Live instructor-led training: 9am – noon PDT
Live office hours and support daily.
Trusted by Leading Companies
HANDS-ON LEARNING
Hands-on Real-time Analytics Training for Everyone
Gain an understanding of the fundamentals of streaming data and the fundamentals of using a stream processing engine to convert streaming data and generate the result to output. Discover how to link your application to a message broker so you can process a massive amount of data without losing any data. In addition, you will learn how to build a real-time pipeline that can ingest data from IoT devices and other services, transform it, and push it to other destinations for additional analysis.
START FROM GROUND UP
Designed for Both Practitioners and Beginners
Before you arrive for the in-person learning experience, our carefully designed self-paced learning modules will help you get up to speed with Python fundamentals.
Beginner in Python or a little rusty with syntax? No problem! Our pre-training learning modules will get you ramped up before the live training.
COMPLETE LEARNING ECOSYSTEM
Instructor-Led Training, Office Hours, Mentoring, and More
- Instructor-led, live training
- Daily, live office hours for homework support
- Hundreds of code samples for practice
- Cloud-based compute tools, inline code editor, and code repositories
- Hundreds of Pandas, NumPy, Seaborn, matplotlib and scikit-learn code samples
- Mentoring for class project
- One-year access to all supplementary learning material
- Verified certificate from The University of New Mexico Continuing Education
Curriculum
Understand the Fundamentals of Events and Event Processing Engines
We will understand various use cases of stream processing and why it is needed. Next, we will discuss the usual components of an event processor. Then, we will use Azure Stream Analytics as an example of how event processors work. This module will also include a hands-on lab involving stream data intake and processing using a stream processor. Finally, we will discuss other popular stream processing platforms.
- Importance and use cases of stream processing
- Components of Event Processor
- Using Azure Stream Analytics as a Stream Processor and understanding its internal architecture
- Process real-time events using Azure Stream Analytics (hands-on)
- Comparing Azure Streams Analytics with similar services in other cloud providers.
Learning outcomes:
In this module, you will:
- Understand the importance and use cases of event processing
- Learn how to process stream data using stream processor
- Learn the internal components of a typical stream processor
- Understand various available platforms for using stream processors
Building Reliable Message Broker for Real-Time Analytics Application
This module will explain a message broker and the commercial and technical issues it can address. Then, we will examine Event Hubs in terms of its numerous components. In addition, there will be a hands-on activity, including the configuration of Event Hubs for data ingestion as scale. Finally, this module will conclude with a comparison of Azure Event Hubs to other message broker services.
Topics:
- Fundamentals of message broker
- Importance of message broker
- Components of message broker
- Using Event Hubs as message broker
- Setup Event Hubs to send and receive messages
- Comparing event hubs with other message brokers
Learning outcomes:
- Understand the importance of message broker
- Learn how to ingest data using message broker
- Learn the components of a typical message broker
- Understand various available open source and platform as a service message brokers
Building reliable message broker for real-time analytics application
Building Scalable Message Broker for IoT Analytics
This module will teach you what makes message brokers for IoT analytics special. We will explore the several components required for feeding telemetry data from IoT devices into the cloud for further insights. We will also do a hands-on lab on building an IoT pipeline for the analytics and maintenance of IoT devices.
Topics:
- The fundamentals of IoT Analytics and its components
- Importance of IoT Analytics
- Io Hub and its internal components
- Hands on: Configuring application to send and receive message through IoT Hub
- Comparing IoT Hub with other similar services
Learning outcomes:
- Understand the fundamentals and use cases of IoT Analytics
- Learn how to ingest data using IoT message broker
- Learn the components of typical IoT message broker
- Understand various available services for IoT message broker.
Hands On: Building Real-Time Analytics Pipeline for Near Real-Time Insights
In this module, we will apply the concepts learned in earlier modules in lab environment:
- We will do a hands-on lab to create a real-time analytics pipeline for social media monitoring.
- We will develop real-time analytics solution for detecting credit card fraud detection
- After collecting data about our weather using IoT devices, we will create the weather forecasting model.
- We will also build a real-time analytics pipeline for collecting data from accelerometers and gyroscopes in smartphones and store it in the cloud for visualization and further insights.
Topics:
- Real-time credit card fraud detection pipeline
- Building the real-time pipeline for social media analytics using message broker and stream processor and visualizing it.
- Build weather forecasting model using IoT data
- Processing IoT Stream data coming from simulated personal device and visualizing it.
Learning outcomes:
- Learn to build real-time credit card fraud detection
- Understand how to build real-time social media analytics
- Learn to build weather forecasting model using IoT data
- Learn to visualize the real-time data collected from the gyroscope, accelerometer, and magnetometer data
Earn a Verified Certificate
Earn a data science certificate from the University of New Mexico, verifying your skills. Step into the market with a proven and trusted skillset.
Earn a Verified Certificate
In association with
Earn a data science certificate from the University of New Mexico, verifying your skills. step into the market with a proven and trusted skillset.
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Amina Tariq
Influitive
Taught by Practitioners
Our instructors are dedicated to helping you steer your career. With years of experience in the field, our instructors are professional data scientists and practitioners. They bring real-world stories and anecdotes to the class, adding immense value to your learning.
FAQs
Access to the program content depends on the plan you choose at the time of registration.
Hands-On Introduction to Real-Time Analytics training is 2 days, 4 hours per day, for a total of 8 hours of training. There is additional practice if you would like to keep refining your python skills after the program ends.
There are no prerequisites for this program, however our pre-course prep work will include tutorials on fundamental concepts of data platform to help you prepare for the training program.
Classes are live and instructor led. The program is not self-paced, but we do provide practical exercises to further facilitate your learning. Lectures will also be recorded to give students the option to go back and review.
The cost will depend on the plan purchased by the students and the discounts available at the time.
Please contact us at [email protected] for updated information on discount availability and payment plans.
We’re offering three different plans for this program.
- Dojo. With the Dojo plan, you will get 8 hours of live training, pre-training material, and program content.
- Guru. With the Guru plan, you will get everything in the Dojo plan including bonus access to the learning platform during the program, access to collaboration forum, recorded live sessions, and a verified data science certificate from the University of New Mexico worth 1 Continuing Education Credits.
- Sensei. With the Sensei plan, you will get everything included in the Guru plan with the addition of one year of access to the learning platform, collaboration forums, recorded sessions and office hours, and live support during the program.
Yes, we are offering an early-bird discount on all three plans.
The class will be 4 hours per day, and you can expect 3-4 hours of homework. Our instructors and teaching assistants will be available during office hours for additional help.
To register for the program, simply view our packages and register for the upcoming cohort. The payment can be made online on our website, via invoice, or wire transfer.
Once you are registered for the program, you will receive a few emails from us. One of those emails will contain steps to create your learning portal account and access the program content.
Please follow the steps in the email to create your account. If you’re facing any difficulty please email us at [email protected] for assistance.
Get in touch
Feel free to ask questions or share your comments with us. We’ll get back to you soon.
You can also reach out to us by phone or email.
If you want to learn more about our trainings, register for an online info session.