|Course or Certification Name||Category||Location||Mode of learning|
|Apache Kafka for Beginners - Learn Kafka by Hands-On||Opensource Server Administration||Online self study|
|The Ultimate Hands-On Hadoop - Tame your Big Data!||Big Data||Online self study|
|Big Data Engineer Course||Big Data||Offline self study|
|Complete Machine Learning and Data Science: Zero to Mastery||Machine Learning||Online self study|
|Cloudera Hadoop Developer||Big Data||Classroom|
|Big Data Hadoop & Spark Developer||Big Data||Online self study|
|Apache Kafka||Big Data||Online self study|
|Senior Software Architect Masters - 200+ courses||Emerging Web Technologies||Online self study|
|Software Masters Program- 200+ courses||Emerging Web Technologies||Online self study|
|Big Data - Post Graduate Program in Data Engineering Course||Big Data||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Apache HBase Fundamentals Certification||Hadoop Administration||Online self study|
|Apache Hadoop and MapReduce Essentials||Big Data||Online self study|
|Scala Programming Course||Big Data||Online self study|
|Big Data Expert||Big Data||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Cloudera Apache Hadoop Administration||Hadoop Administration||Online self study|
Description: Learn the fundamentals and advanced concepts of Apache Kafka in this course. There will be a hands on for each concept using inbuilt shell scripts that are available inside the Kafka download and using Java, Camel,Spark Spring Boot and Docker . This course will walk you through the concepts step by step and immediate hands on for each topic discussed. This course will help increase your technical expertise in Kafka. This course will be an eyeopener for people think Kafka is a complex system, eventually you will understand how simple Kafka is. This course can be a career breakthrough and assure you that you will find yourself in a better place after you complete this course. This course will transfer your from novice Kafka user to a experienced Kafka user. Why I should take this course ? This course will walk you through the Kafka architecture, different components of the Kafka architecture and advantages of Kafka over other systems. This course will focus on the internals of the Kafka and how to use Kafka and implement the concepts that are learnt in real time. This course will teach you how to implement the concepts using Java, Camel, Spark, Spring Boot and Docker. Course Overview: Section 1: Getting Started This section explains about the author and the course objectives. Section 2: Kafka Architecture This section explains about the following: Why do you need Kafka ? What is Kafka ? Kafka Architecture and the different components in the Kafka architecture. Role of zookeeper, Kafka Broker, Kafka Cluster, Producers and Consumers. Section 3: Download Kafka This sections explored about the different approaches of downloading the Kafka distribution in your local. Section 4: Core Internals of Apache Kafka + Hands on This section shows you the demo on how to start zookeeper and Kafka broker. Detailed explanation about Topics, Partitions, Consumers and Producers. Hands on creating topic and how to connect producer and consumers to the created topic using Console Producer and Consumer . Hands on about Kafka commit log. Section 5 : Kafka API's This section explains about the different Core API's and its use cases. Section 6 : Behind the scenes zookeeper, Broker , Producer and Consumers This section explains about what are the different Kafka components that interact with each to create a topic using a flow diagram . This sections also covers how producers and consumers connect to the Kafka and what are the different components that interact with each other behind the scenes. Section 7 : Running Multiple Brokers Hands on how to run multiple brokers in your machine. How does the consumer and producer while running it against the multiple brokers. Hands on Leader, Replica and ISR attributes in a Topic. Section 8 : Kafka Producers Detailed explanation about Kafka Producer and how to connect to the Kafka Cluster. How to implement the Kafka producer using Java? Exploring different partitioning mechanism and implementation in Java. How to alter the configuration of a topic ? Section 9 : Kafka Consumer Detailed explanation about Kafka Consumer. How to implement the Kafka Consumer using Java? Different types of Offset Management in Kafka Consumer. Automatic Offset Management using Java. Manual Offset Management using Java. Consumer Groups in Kafka consumer and its Advantages. Consumer Group id and its benefits. Implementation of consumer group in Java. How to reset the offset to a particular value in Kafka Consumer ? Section 10: Kafka Client - GUI Tool In this section we will download, install and demo about the Kafka GUI client tool that will be used to connect and Manage the Kafka cluster. Section 11: Apache Camel + Kafka Integrationa Quick Introduction to Apache Camel Apache Camel simple example Apache Camel Architecture Hands on - How to Build a Kafka consumer using Apache Camel Framework ? Hands on - How to Build a Kafka producer using Apache Camel Framework ? Section 12: Apache Spark + Kafka Integrationa Quick Introduction to Apache Spark Hands on - How to Build a Kafka consumer using Apache Spark Framework ? Section 12: Additional Configurations How to delete a topic ? Section 13: Apache Kafka -Spring Boot Implementation This section explains about the Spring boot Implementation of Apache Kafka modules Quick Introduction to Spring Quick Introduction to Spring boot Simple Spring Boot App via hands on Kafka Consumer using Spring Boot Kafka Producer using Spring Boot Section 14: Docker - Dockerize Kafka Broker, Zookeeper, Producer and Consumer In this section we will run the dockerized version of kafka broker, zookeeper and we will create the docker image of the Spring boot App. Quick Introduction to Docker. Installation of Docker Tool Box on Windows 10. Installation of Docker Tool Box on Mac. Creating a docker image of the spring boot App Creating an Account in Docker Hub and push/pull from Docker Hub. Exploring Different Docker commands. How to run Kafka Broker/Zookeeper in Docker ? Complete Integration and working app of Dockerized Kafka Broker, Zookeeper and dockerized Spring boot app. Section 15: Apache Kafka Security and Authentication In this section we will explore about the Kafka security Why do you need Kafka security ? Hands on session on how to enable SSL in Kafka Broker ? Hands on session on how to access the SSL secured broker using Console Consumer/Producer ? Hands on session on how to configure SSL in Kafka Producer using Java ? Hands on Session on how to configure SSL in Kafka Consumer using Java ? How to delete a topic ? Section 16: Conclusion Congratulations and Thank You ! By the end of this you will have a complete understanding of how Apache Kafka works and how to implement the concepts in real time using Java, Apache Camel, Apache Spark , Spring Boot and Docker.
The world of Hadoop and "Big Data" can be intimidating - hundreds of different technologies with cryptic names form the Hadoop ecosystem. With this Hadoop tutorial, you'll not only understand what those systems are and how they fit together - but you'll go hands-on and learn how to use them to solve real business problems! Learn and master the most popular big data technologies in this comprehensive course, taught by a former engineer and senior manager from Amazon and IMDb . We'll go way beyond Hadoop itself, and dive into all sorts of distributed systems you may need to integrate with. Install and work with a real Hadoop installation right on your desktop with Hortonworks (now part of Cloudera) and the Ambari UI Manage big data on a cluster with HDFS and MapReduce Write programs to analyze data on Hadoop with Pig and Spark Store and query your data with Sqoop , Hive , MySQL , HBase , Cassandra , MongoDB , Drill , Phoenix , and Presto Design real-world systems using the Hadoop ecosystem Learn how your cluster is managed with YARN , Mesos , Zookeeper , Oozie , Zeppelin , and Hue Handle streaming data in real time with Kafka , Flume , Spark Streaming , Flink , and Storm Understanding Hadoop is a highly valuable skill for anyone working at companies with large amounts of data. Almost every large company you might want to work at uses Hadoop in some way, including Amazon, Ebay, Facebook, Google, LinkedIn, IBM, Spotify, Twitter, and Yahoo! And it's not just technology companies that need Hadoop; even the New York Times uses Hadoop for processing images. This course is comprehensive, covering over 25 different technologies in over 14 hours of video lectures . It's filled with hands-on activities and exercises, so you get some real experience in using Hadoop - it's not just theory. You'll find a range of activities in this course for people at every level. If you're a project manager who just wants to learn the buzzwords, there are web UI's for many of the activities in the course that require no programming knowledge. If you're comfortable with command lines, we'll show you how to work with them too. And if you're a programmer, I'll challenge you with writing real scripts on a Hadoop system using Scala, Pig Latin, and Python . You'll walk away from this course with a real, deep understanding of Hadoop and its associated distributed systems, and you can apply Hadoop to real-world problems. Plus a valuable completion certificate is waiting for you at the end! Please note the focus on this course is on application development, not Hadoop administration. Although you will pick up some administration skills along the way. Knowing how to wrangle "big data" is an incredibly valuable skill for today's top tech employers. Don't be left behind - enroll now! "The Ultimate Hands-On Hadoop... was a crucial discovery for me. I supplemented your course with a bunch of literature and conferences until I managed to land an interview. I can proudly say that I landed a job as a Big Data Engineer around a year after I started your course. Thanks so much for all the great content you have generated and the crystal clear explanations. " - Aldo Serrano "I honestly wouldnâ€š be where I am now without this course. Frank makes the complex simple by helping you through the process every step of the way. Highly recommended and worth your time especially the Spark environment. This course helped me achieve a far greater understanding of the environment and its capabilities. Frank makes the complex simple by helping you through the process every step of the way. Highly recommended and worth your time especially the Spark environment." - Tyler Buck
This Big Data Engineer Masterâ€™s Program in collaboration with IBM provides training on the popular skills required for a successful career in data engineering. Master the Hadoop Big Data framework, leverage the functionality of Apache Spark with Python, simplify data lines with Apache Kafka and use the database management tool MongoDB to store data.
Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 180,000+ developers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. This is a brand new Machine Learning and Data Science course just launched January 2020! Graduates of Andrei's courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, + other top tech companies. Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know). This comprehensive and project based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want. The curriculum is going to be very hands on as we walk you from start to finish of becoming a professional Machine Learning and Data Science engineer. The course covers 2 tracks. If you already know programming, you can dive right in and skip the section where we teach you Python from scratch. If you are completely new, we take you from the very beginning and actually teach you Python and how to use it in the real world for our projects. Don't worry, once we go through the basics like Machine Learning 101 and Python, we then get going into advanced topics like Neural Networks, Deep Learning and Transfer Learning so you can get real life practice and be ready for the real world (We show you fully fledged Data Science and Machine Learning projects and give you programming Resources and Cheatsheets)! The topics covered in this course are: - Data Exploration and Visualizations - Neural Networks and Deep Learning - Model Evaluation and Analysis - Python 3 - Tensorflow 2.0 - Numpy - Scikit-Learn - Data Science and Machine Learning Projects and Workflows - Data Visualization in Python with MatPlotLib and Seaborn - Transfer Learning - Image recognition and classification - Train/Test and cross validation - Supervised Learning: Classification, Regression and Time Series - Decision Trees and Random Forests - Ensemble Learning - Hyperparameter Tuning - Using Pandas Data Frames to solve complex tasks - Use Pandas to handle CSV Files - Deep Learning / Neural Networks with TensorFlow 2.0 and Keras - Using Kaggle and entering Machine Learning competitions - How to present your findings and impress your boss - How to clean and prepare your data for analysis - K Nearest Neighbours - Support Vector Machines - Regression analysis (Linear Regression/Polynomial Regression) - How Hadoop, Apache Spark, Kafka, and Apache Flink are used - Setting up your environment with Conda, MiniConda, and Jupyter Notebooks - Using GPUs with Google Colab By the end of this course, you will be a complete Data Scientist that can get hired at large companies. We are going to use everything we learn in the course to build professional real world projects like Heart Disease Detection, Bulldozer Price Predictor, Dog Breed Image Classifier, and many more . By the end, you will have a stack of projects you have built that you can show off to others. Here's the truth: Most courses teach you Data Science and do just that. They show you how to get started. But the thing is, you don't know where to go from there or how to build your own projects. Or they show you a lot of code and complex math on the screen, but they don't really explain things well enough for you to go off on your own and solve real life machine learning problems. Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don't know what to do other than watch another tutorial. No! This course will push you and challenge you to go from an absolute beginner with no Data Science experience, to someone that can go off, forget about Daniel and Andrei, and build their own Data Science and Machine learning workflows. Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career. You hear statements like Artificial Neural Network, or Artificial Intelligence (AI), and by the end of this course, you will finally understand what these mean! Click Enroll Nowand join others in our community to get a leg up in the industry, and learn Data Scientist and Machine Learning. We guarantee this is better than any bootcamp or online course out there on the topic. See you inside the course! Taught By: Andrei Neagoie is the instructor of the highest rated Development courses on Udemy as well as one of the fastest growing. His graduates have moved on to work for some of the biggest tech companies around the world like Apple, Google, Amazon, JP Morgan, IBM, UNIQLO etc... He has been working as a senior software developer in Silicon Valley and Toronto for many years, and is now taking all that he has learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer allows in life. Having been a self taught programmer, he understands that there is an overwhelming number of online courses, tutorials and books that are overly verbose and inadequate at teaching proper skills. Most people feel paralyzed and don't know where to start when learning a complex subject matter, or even worse, most people don't have $20,000 to spend on a coding bootcamp. Programming skills should be affordable and open to all. An education material should teach real life skills that are current and they should not waste a student's valuable time. Having learned important lessons from working for Fortune 500 companies, tech startups, to even founding his own business, he is now dedicating 100% of his time to teaching others valuable software development skills in order to take control of their life and work in an exciting industry with infinite possibilities. Andrei promises you that there are no other courses out there as comprehensive and as well explained. He believes that in order to learn anything of value, you need to start with the foundation and develop the roots of the tree. Only from there will you be able to learn concepts and specific skills(leaves) that connect to the foundation. Learning becomes exponential when structured in this way. Taking his experience in educational psychology and coding, Andrei's courses will take you on an understanding of complex subjects that you never thought would be possible. See you inside the course!
Hadoop Developer certification will let students create robust data processing applications using Apache Hadoop. After completing this course, students will be able to comprehend workflow execution and working with APIs by executing joins and writing MapReduce code. This course will offer the most excellent practice environment for the real-world issues faced by Hadoop developers. Hadoop developers are among the world's most in-demand and highly-compensated technical roles. According to a McKinsey report, US alone will deal with shortage of nearly 190,000 data scientists and 1.5 million data analysts and Big Data managers by 2018
Spark Core provides basic I/O functionalities, distributed task dispatching, and scheduling. Resilient Distributed Datasets (RDDs) are logical collections of data partitioned across machines. RDDs can be created by referencing datasets in external storage systems, or by applying transformations on existing RDDs. In this course, you will learn how to improve Spark's performance and work with Data Frames and Spark SQL. Spark Streaming leverages Spark's language-integrated API to perform streaming analytics. This design enables the same set of application code written for batch processing to join streams against historical data, or run ad-hoc queries on stream state. In this course, you will learn how to work with different input streams, perform transformations on streams, and tune up performance. MLlib is Spark's machine learning library. GraphX is Spark's API for graphs and graph-parallel computation. SparkR exposes the API and allows users to run jobs from the R shell on a cluster. In this course, you will learn how to work with each of these libraries.
Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. Professionals who are interested in big data or data analysis career can learn this tool. | This Apache Kafka course provides the candidates with the basic concepts and in-depth understanding of how to deploy it | The course also offers candidates skills on managing servers, data serialization and deserialization techniques, and strategies for testing Kafka | Designed by some of the best professionals in the industry, the course offers quality online learning modules | Upon successful completion, a certification is offered to the candidates
Evolved and designed by veterans in the Analytics industry, this program prepares students and working professionals to start or improve upon a career in the growing Data and Analytics domain. A perfect blend of technology, Data science and business cases and insights, the program stands out as among the best in the world. | This is a career oriented program that covers all the key aspects of Data Engineering. A great feature is the flexibility in the program to assimilate and incorporate technology updates into the modules, on the fly. This program also comes with the benefit of Placement support from 361 Degree Minds though you would not have the need since opportunities galore when you do this program. | We follow world class adult and remote learning methodologies. This ensures that the learning outcome of the program meets individual aspirations as well as market / industry expectations. | This program also equips you with a thorough knowledge on various Big Data Technologies including Hadoop, R, Python, Spark, RDBMS tools and a wide range of Access tools.
Apache HBase is an open-source, non-relational, distributed database modelled after Google's BigTable and is written in Java. It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System), providing BigTable-like capabilities for Hadoop. This Apache HBase Fundamentals course will provide the candidates with the skills and knowledge on how to install HBase and discusses the HBase architecture and data modelling designs. The course offers unlimited access to the candidates for six months and a course completion certificate, which is recognised all across the world. Providing a career boost for both students and professionals, the modules have been designed by experts in the industry.
A set of algorithms for distributed processing of large data sets on computer clusters built from commodity hardware dubbed as Apache Hadoop. This course provides an introduction on the basic concepts of cloud computing with the help Apache Hadoop, Big Data and cloud computing. It also includes high-level information about operation, concepts, architecture and Hadoop ecosystem. MapReduce programming used for processing parallelizable issues across huge datasets. The course will take you through basics of programming in MapReduce and Hive. This training program is packed with case studies and real-life projects so that you gain a complete knowledge of apache Hadoop and MapReduce.
Scala is a flexible object oriented as well as a functional programming language. Learn and master the basic concepts of Scala such as variables, strings, loops, etc. in this online training course, which will enable you to utilize its robust, simple, and powerful performance features to the fullest. | This online Scala programming course is for beginners introduces the learners to the fundamentals of Scala.The course will help students understand variables, conditionals, loops, functions, and classes present in Scala.
Hadoop is an Apache project (i.e. an open source software) to store & process Big Data. Hadoop stores Big Data in a distributed & fault tolerant manner over commodity hardware. Afterwards, Hadoop tools are used to perform parallel data processing over HDFS (Hadoop Distributed File System) | As organisations have realized the benefits of Big Data Analytics, so there is a huge demand for Big Data & Hadoop professionals. Companies are looking for Big data & Hadoop experts with the knowledge of Hadoop Ecosystem and best practices about HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop & Flume | Edureka Hadoop Training is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop Ecosystem. This Hadoop developer certification training is stepping stone to your Big Data journey and you will get the opportunity to work on various Big data projects.
Cloudera Apache Hadoop Administration training will help students comprehend the storage management, Hadoop filesystem, creation and management of Hadoop cluster. This Hadoop course includes all tools which are useful for achieving Hadoop admin certification. Students will be able to learn the practices and concepts required to introduce Hadoop into an organization, from configuration and installation to load balancing and tuning to solving and diagnosing problems in the deployment.