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A List Of The Top 12 Online Courses And Training Programs For Big Data In 2022

Writer : Mis. Rossela Ilkan

Best practices and techniques for dealing with big data are becoming increasingly important in the workplace. Organizations are scrambling to make the most of their data architectures as the big data landscape continues to change in real time. Along with this, Hadoop and the data lake have emerged as technologies that no company can ignore, as they complement the data warehouse quite well, or may even be replaced by it in some cases

If you're looking to improve your data management or analytics skills, we've put together this list of the best big data courses and online training. Not an exhaustive list, but a selection of the best online big data courses and training from well-known providers is provided here as a starting point. For your convenience, we've included a list of relevant courses on each platform, along with a link to further reading.

Some of the Best Big Data Courses

Data Science as a Specialty (UC San Diego)

Coursera's Big Data Specialization for Beginners takes about 8 months to complete and requires no prior knowledge. Upon completion, students are given a certificate that can be shared with others.

Training ground: Coursera

Hands-on experience with big data tools and systems will help you gain a better understanding of what insights big data can provide. If you've never programmed before, that's fine! You will learn how to use MapReduce, Spark, Pig, and Hive in Hadoop. Predictive modeling and graph analytics for problem modeling can be learned by following along with the provided code.

PySpark: The Foundations of Big Data Analysis

The DataCamp Big Data Fundamentals course will introduce you to the fundamentals of working with big data and PySpark. It includes four hours of training, 16 videos, and 55 exercises.

DataCamp is the platform used for this exercise.

Description: PySpark is used in this course to teach the basics of Big Data. When it comes to Big Data, Spark is a "lightning-fast cluster computing" platform. You can run programs up to 100 times faster in memory or 10 times faster on disk with it than with Hadoop's general data processing platform engine. Programming in Python using SparkSQL, MLlib (for machine learning), etc. will be used to interact with William Shakespeare's works and analyze Fifa football 2018 data as well as perform genomic dataset clustering.

Training for the Big Data Hadoop Certification

All of the components of the Hadoop ecosystem are covered in this module, including its architecture, the MapReduce framework, and more.

Adopting Edureka as a platform

Hadoop experts have curated Edureka's Big Data Hadoop Certification Training course, which covers in-depth knowledge of big data and the Hadoop ecosystem tools such as HDFS, YARN, MapReduce, Hive and Pig, HBase, Spark, Oozie, Flume and Sqoop. Edureka's Cloud Lab will be used throughout this online instructor-led Hadoop training to help you work on real-world industry use cases.

Big Data and Knowledge Management in the Workplace

We think the edX Knowledge Management course is a great place to start if you're new to the field. It takes about 8 weeks to complete. They are Hong Kong Polytechnic University professors Eric Tsui and W.B. Lee, respectively.

edX is the platform used for this course.

Description: The Hong Kong Polytechnic University's Knowledge Management and Innovation Research Center (KMIRC) provides this course. The international alliances the KMIRC has formed with leading practitioners, many of whom are considered members of the "Hall of Fame" in knowledge management and are well-known around the world, further strengthen its capabilities and competencies. A background in humanities, management, social science or engineering is required for participation in this course.

What Every Manager Should Know About Big Data

OUR TAKE: This course shows students how big data is used in the real world and the return on investment it provides, which can help managers make better decisions about the use, resourcing, risks, and value of big data.

The Experiment platform

Non-technical terms are used in this course to help students understand and demystify big data. Bridges the gap between the hype of the market and the realities of business. It outlines the successes and failures of big data, as well as the reasons for both, in the real world. With this course, you'll learn how to make smart decisions about the use, resourcing, risks, and value of big data based on what you'll learn in this course.

Big Data Analytics certification

Data analysts, software engineers, and project managers are the target audience for this course, which focuses on data analytics and data science. There are more than 230 hours of on-demand learning in the course, which takes about nine months to complete.

Informatization: IntelliPaat.

In collaboration with E&ICT, IIT, Guwahati, this program aims to provide extensive training on Big Data Analytics concepts like Hadoop, Spark; Python; MongoDB; data warehousing; and more. Students should be able to understand the concepts, master them thoroughly, and apply them in real-world situations as a result of this program.

 

 Big Data Engineering with Apache Spark

OUR POINT OF VIEW: This course, taught by industry veteran Kumaran Ponnambalam, covers topics such as using Spark and Kafka for data engineering, moving data with Kafka, understanding how Spark works, and building complex accumulators.

LinkedIn is the preferred platform. In this course, you'll learn how to build Apache Spark-based big data pipelines. You'll learn how to integrate Apache Spark with other big data technologies with Kumaran Ponnambalam's help. To enable real-time streaming, he walks through the fundamentals of Apache Kafka Connect and shows how to do so with Spark. In addition, he demonstrates how to build an end-to-end project that solves a real-world business problem with the help of various technologies.

 

The AWS Big Data Training Program

OUR TAKE: The Mindmajix specialty certification training consists of 30 hours of live training, 20 hours of lab sessions, and a flexible schedule to work with. Designed by a team of experts in the field of big data.

Mindmajix is the platform.

With real-world examples, you'll learn how to design and manage big data solutions on the AWS platform. During your training, you will have the opportunity to work on real-world projects based on real-world industry needs, which will help you earn your AWS big data developer certification.

 

 The Big Picture: Big Data

Learn about big data concepts, major technologies, and the most popular software tools with this intermediate-level Pluralsight training. Andrew Brust, a seasoned professional in the field, teaches the course.

Pluralsight is the platform used.

Andrew Brust, a big data correspondent for ZDNet, walks you through the basics of big data. These definitions and technologies as well as the vendors you should be familiar with will all be covered in this course. There are many advantages to utilizing big data, including the ability to combine it with traditional database and Business Intelligence (BI) technologies, as well as the ability to create a plan for your company's implementation of these technologies.

 

 The Master's Program in Big Data Engineering

More than 120 hours of live, interactive learning, a capstone, and 15 real-world projects are included in this program. For each course successfully completed, students receive a certificate.

Implementation: Simplilearn

In collaboration with IBM, this Big Data Engineer Master's Certification program provides online training on the best big data courses to impart the skills needed for a successful career in data engineering. Master the Hadoop and big data frameworks, take advantage of AWS services, and store data in the MongoDB relational database management system.

 

 Use Spark and Python together with PySpark for Big Data applications.

We think this is one of the most popular and highly rated big data courses on the internet, with nearly 15,000 reviews and 4.5 stars. More than ten hours of video on-demand, four articles, and four downloadable resources are all available here.

Udemy is the preferred platform.

A crash course in Python will be followed by instruction on how to use Spark DataFrames and the newest Spark 2.0 syntax in this introductory course. Next, we'll cover the MLlib Machine Library and how to use the DataFrame syntax with Spark. Every step of the way, exercises and simulated consulting projects will put you in a position to apply what you've learned in a real-world setting.

 

The Nanodegree Program in Data Engineering

OUR OUTCOME: Students will gain the knowledge and abilities necessary to design and implement data infrastructure that is ready for production. As little as five months are required to complete this course module. Intermediate Python and SQL skills are required.

Udacity, as a platform

In this course, you will learn how to design data models, build data warehouses, and automate data pipelines. With your new knowledge, you'll complete a capstone project at the end of the program. Intermediate Python and SQL skills are required for success in this program.

 

 

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