Download and Learn Data Streaming Udacity Nanodegree Course 2023 for free with google drive download link.
Learn the skills to take you into the next era of data engineering. Build real-time applications to process big data at scale.
What You’ll Learn in Data Streaming Nanodegree
Data Streaming
Estimated 2 Months to complete
Learn how to process data in real-time by building fluency in modern data engineering tools, such as Apache Spark, Kafka, Spark Streaming, and Kafka Streaming.
You’ll start by understanding the components of data streaming systems. You’ll then build a real-time analytics application. Students will also compile data and run analytics, as well as draw insights from reports generated by the streaming console.
Data Streaming Intro Video:
Prerequisite knowledge
To be successful in this program, you should have intermediate Python and SQL skills, as well as experience with ETL.
The Data Streaming Nanodegree program is designed for students with intermediate Python and SQL skills, as well as experience with ETL. Basic familiarity with traditional batch processing and basic conceptual familiarity with traditional service architectures is desired, but not required.
Intermediate Python programming knowledge, of the sort gained through the Programming for Data Science Nanodegree program, other introductory programming courses or programs, or additional real-world software development experience. Including:
- Strings, numbers, and variables; statements, operators, and expressions;
- Lists, tuples, and dictionaries; Conditions, loops;
- Procedures, objects, modules, and libraries;
- Troubleshooting and debugging; Research & documentation;
- Problem solving; Algorithms and data structures
Intermediate SQL knowledge and linear algebra mastery, addressed in the Programming for Data Science Nanodegree program, including:
- Joins, Aggregations, and Subqueries
- Table definition and manipulation (Create, Update, Insert, Alter)
Foundations of Data Streaming
Learn the fundamentals of stream processing, including how to work with the Apache Kafka ecosystem, data schemas, ApacheAvro, Kafka Connect and REST proxy, KSQL, and Faust Stream Processing.
Project – Optimize Chicago Public Transit
In this project, students will stream public transit status, using Kafka and the Kafka ecosystem, to build a stream processing application that shows the status of buses and trains in real time. Students will learn how to have their own Python code produce events, use REST Proxy to send events over HTTP, and set up Kafka Connect to collect data from a Postgres database. Finally, students will utilize the Faust Python Stream Processing library to transform station data.
Streaming API Development and Documentation
The goal of this course is to grow your expertise in the components of streaming data systems, and build a real time analytics application. Specifically, you will be able to identify components of Spark Streaming (architecture and API), build a continuous application with Structured Streaming, consume and process data from Apache Kafka with Spark Structured Streaming (including setting up and running a Spark Cluster), create a DataFrame as an aggregation of source DataFrames, sink a composite DataFrame to Kafka, and visually inspect a data sink for accuracy.
Project – Evaluate Human Balance with Spark Streaming
In this project, you will work with a real-life application called the Step Trending Electronic Data Interface (STEDI). It is a working application used to assess fall risk for seniors. When a senior takes a test, they are scored using an index which reflects the likelihood of falling, and potentially sustaining an injury in the course of walking. STEDI uses a Redis datastore for risk score and other data. The Data Science team has completed a working graph for population risk at a STEDI clinic. The problem is the data is not populated yet. You will work with Kafka Connect Redis Source events and Business Events to create a Kafka topic containing anonymized risk scores of seniors in the clinic.
Data Engineer is one of the best jobs for 2019, with a base salary of $100k.
All our programs include:
Real-world projects from industry experts
With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.
Technical mentor support
Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you and keeping you on track.
Career services
You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.
Flexible learning program
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
❗❗ Important Must Read ❗❗
Regarding Google Drive, we are only accepting 100 file requests per day because Google has banned our Drive account from publicly sharing larger files. Additionally, some websites are using our files without giving us credit also Google Allows only limited no of downloads per day. So we’ve made the course material / file private; you can request it, but it’s first come, first served. We are currently receiving over 6000+ file requests per day.
However, you can pay only $99 We’ll provide a Dedicated Drive Folder with all 79 updated Udacity Courses in it, Also you can request course and we’ll add them into your Dedicated Drive Folder.
If you think it’s too expensive, consider this: if you enroll in Udacity, a single Nanodegree Course will cost you $300 per month, but we’re offering it for $99 for 79 Nanodegree Courses + Requesting Courses too, that you can download and access whenever you want (Lifetime Access) and We are also paying for Google Drive Storage, by considering all that we have set the price at $99, This Price is only for Limited Period, we might increase the price in future
Contact: [email protected] for Dedicated drive link. Our Team will respond to the mail within 24 hours with the payment and other details or for faster support Contact us on Telegram: @probono42.
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