Big Data Courses with Its famous Frameworks: Apache, Hadoop, etc

By ridhigrg |Email | Aug 6, 2019 | 7221 Views

Data Engineering, Big Data, and Machine Learning on GCP Specialization
Data Engineering on Google Cloud Platform. Launch your career in Data Engineering. Deliver business value with big data and machine learning.
About this Specialization
This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data.

This course teaches the following skills:
  • Design and build data processing systems on the Google Cloud Platform
  • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc
  • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow
  • Derive business insights from extremely large datasets using Google BigQuery
  • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML
  • Enable instant insights from streaming data
  • This class is intended for developers who are responsible for:
  • Extracting, Loading, Transforming, cleaning, and validating data
  • Designing pipelines and architectures for data processing
  • Creating and maintaining machine learning and statistical models
  • Querying datasets, visualizing query results and creating reports

Introduction to Big Data
About this Course
Interested in increasing your knowledge of the Big Data landscape?  This course is for those new to data science and interested in understanding why the Big Data Era has come to be.  It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems.  It is for those who want to start thinking about how Big Data might be useful in their business or career.  It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible-increasing the potential for data to transform our world!

This course is for those new to data science.  No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments.  

Hardware Requirements:
(A) Quad-Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking About This Mac. Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements. You will need a high-speed internet connection because you will be downloading files up to 4 Gb in size.  

Software Requirements:
This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.

Big Data for Data Engineers Specialization
Build Your Data Engineering Skills. Learn how to tame the big data beast with the most popular tools assisted by top-notch practitioners
About this Specialization
This specialization is made for people working with data (either small or big). If you are a Data Analyst, Data Scientist, Data Engineer or Data Architect (or you want to become one) - don't miss the opportunity to expand your knowledge and skills in the field of data engineering and data analysis on the large scale.

In four concise courses, you will learn the basics of Hadoop, MapReduce, Spark, methods of offline data processing for warehousing, real-time data processing, and large-scale machine learning. And Capstone project for you to build and deploy your own Big Data Service (make your portfolio even more competitive).

Over the course of the specialization, you will complete progressively harder programming assignments (mostly in Python). Make sure, you have some experience in it. This course will master your skills in designing solutions for common Big Data tasks:
  • creating a batch and real-time data processing pipelines,
  • doing machine learning at scale,
  • deploying machine learning models into a production environment - and much more!

Join some of the best hands-on big data professionals, who know, their job inside-out, to learn the basics, as well as some tricks of the trade, from them.

Modern Big Data Analysis with SQL Specialization
Learn Data Analysis for Big Data. Master using SQL for data analysis on distributed big data systems

About this Specialization
This Specialization teaches the essential skills for working with large-scale data using SQL.

Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you.

Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that's being generated is too big to be stored there, and it's growing too quickly to be efficiently stored in commercial data warehouses. Instead, it's increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable.

To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open-source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines.

This Specialization is designed to provide excellent preparation for the Cloudera Certified Associate (CCA) Data Analyst certification exam. You can earn this certification credential by taking a hands-on practical exam using the same SQL engines that this Specialization teaches-Hive and Impala.

Emerging Technologies: From Smartphones to IoT to Big Data Specialization
Launch Your Career in Advanced Emerging Technology. Master advanced technologies and market trends to lead future R&D and business.
About this Specialization
This Specialization is intended for researchers and business experts seeking state-of-the-art knowledge in advanced science and technology. The 4 courses cover details on Big Data (Hadoop, Spark, Storm), Smartphones, Smart Watches, Android, iOS, CPU/GPU/SoC, Mobile Communications (1G to 5G), Sensors, IoT, Wi-Fi, Bluetooth, LP-WAN, Cloud Computing, AR (Augmented Reality), Skype, YouTube, H.264/MPEG-4 AVC, MPEG-DASH, CDN, and Video Streaming Services. The Specialization includes projects on Big Data using IBM SPSS Statistics, AR applications, Cloud Computing using AWS (Amazon Web Service) EC2 (Elastic Compute Cloud), and Smartphone applications to analyze mobile communication, Wi-Fi, and Bluetooth networks. The course contents are for expert level research, design, development, industrial strategic planning, business, administration, and management.

Source: HOB