Big Data Complete Course
What you'll learn
- Big Data
- Big Data Enabling Technologies
- Hadoop Stack for Big Data
- Hadoop Distributed File System (HDFS)
- Hadoop MapReduce with Example
- Parallel Programming with Spark
- Spark Built-in Libraries
- Data Placement Strategies
- CAP Theorem
- Design of Zookeeper
- CQL (Cassandra Query Language)
- Spark Streaming and Sliding Window Analytics
- Machine Learning
- Machine Learning Algorithm K-means using Map Reduce for Big Data Analytics
- Decision Trees for Big Data Analytics
- Predictive Analytics
- Spark GraphX & Graph Analytics
- Eager to learn Big data.
Big data is a combination of structured, semi structured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modelling and other advanced analytics applications.
Systems that process and store big data have become a common component of data management architectures in organizations, combined with tools that support big data analytics uses. Big data is often characterized by the three V's:
the large volume of data in many environments;
the wide variety of data types frequently stored in big data systems; and
the velocity at which much of the data is generated, collected and processed.
Big data is a great quantity of diverse information that arrives in increasing volumes and with ever-higher velocity.
Big data can be structured (often numeric, easily formatted and stored) or unstructured (more free-form, less quantifiable).
Nearly every department in a company can utilize findings from big data analysis but handling its clutter and noise can pose problems.
Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins.
Big data is most often stored in computer databases and is analysed using software specifically designed to handle large, complex data sets.
Topics Covered in these course are:
Big Data Enabling Technologies
Hadoop Stack for Big Data
Hadoop Distributed File System (HDFS)
Parallel Programming with Spark
Spark Built-in Libraries
Data Placement Strategies
Data Placement Strategies
Design of Zookeeper
CQL (Cassandra Query Language)
Design of HBase
Spark Streaming and Sliding Window Analytics
Big Data Machine Learning
Machine Learning Algorithm K-means using Map Reduce for Big Data Analytics
Parallel K-means using Map Reduce on Big Data Cluster Analysis
Decision Trees for Big Data Analytics
Big Data Predictive Analytics
PageRank Algorithm in Big Data
Spark GraphX & Graph Analytics
Case Studies of big companies and how they operate.
Who this course is for:
- Software engineers
Edcorner provides customer-focused training options in multiple formats and delivery methods, offering individuals and organizations top-quality training that can be tailored to meet individual learning styles and specific needs, such as Online training, Customized training, self paced training, onsite training.
Our instructors are highly qualified and industry experts from across the domain.
Edcorner offers training for following skillsets:
1. HR & HR Analytics, Workday HCM.
2. Programming - C, C++, C sharp, JAVA, JS, Angular, Python, HTML CSS. PHP, Flutter, vb.net, .net, Unity and much more.
3. Cyber security.
8. Project Management