Top 8 Data Analytics Courses at Edureka With Live Training
Edureka is known for its course offerings in Big Data. Every course they offer will be done online. You will learn from 10+ years of industry experts. After getting certification from Edureka, you will understand the actual benefits. Every project you do there at the institute is relevant and industry-specific. Different courses have different offerings, you need to visit their website to learn more. In this article, you will learn about the most popular data analytics courses at Edureka.
About Data Analytics Courses at Edureka
The institute offers two types of course offerings like certification courses and role-based courses. You have to choose which live online courses you want to unlock future benefits. Big data is the most important thing in data analytics. You have to learn the process to get the certificate. They always try to have transparency among the satisfied learners. Choose every course detail as per your requirements. This institution offers all types of technology-related courses. Most of them are live courses and certified courses. Few courses collaborate with universities.
Training Features about Data Analytics Courses at Edureka
- Mostly the course will take 30 to 36 hours of online live instructor lead classes. You will get weekend and weekday classes.
- You will get to understand the process of real-life case studies.
- At every class end, you will submit one assignment.
- You will get lifetime access to class materials and available other benefits.
- The team will give 24 X 7 guidance.
- After completing the final course, you can become a big data expert.
- You will get to join a professional forum to understand trendy news from industry experts.
- You will need 8 GB RAM in a laptop or computer is a must. If you have any query about the required configuration, you can ask the administration department.
Top 7 Data Analytics Courses at Edureka
1. Learn Details About Data Analytics Master Program
This course provides in-depth knowledge and training on data analytics with R and tableau part. The comprehensive program covers almost all parts that require in the present market. You will learn advanced SAS procedures and other different skills. You will attain both self-paced and live online classes. After joining their course you can take weekday or weekend classes at your convenient time. It is regarded as one of the most sought-after data analytics courses at Edureka.
Course Details
● Statistics are essential for analytics.
● Data analytics with R programming.
● Tableau.
● Microsoft Power BI.
● AWS S3
● Data Analytics Capstone project.
Course Fees
INR 59.999
Per Month EMI
INR 6,667
2. Learn Details About Big Data Hadoop Certification Training Course
The institution shares that as per indeed.com the big data Hadoop developer’s salary is $135,00. Every renowned company are hiring for that position. You get to learn and get access to their cloud lab for 60 days. You will learn about the benefits and the high demand for professionals in the market. Their certification courses provide you with the opportunity to learn about various segments and complete every assignment to learn about Hadoop architecture. You will learn and understand the distributed process to use different types of tools. While searching data analytics courses at Edureka, this course structure can be suitable for you.
Course Details
Understand Big Data and Hadoop
- Introduction to big data challenges and big data.
- Limitations and solutions of big data architecture.
- Hadoop and its feature.
- Hadoop ecosystem.
- Hadoop 2. x core components.
- Hadoop storage.
- Hadoop processing: map-reduce framework.
- Different Hadoop distributions.
Hadoop Architecture and HDFS
- Hadoop 2. X cluster architecture.
- Federation and high availability architecture.
- Typical production Hadoop cluster.
- Hadoop cluster modes.
- Common Hadoop shell commands.
- Hadoop 2. X configuration files.
- Single-node cluster and multi-node cluster set-up.
- Basic Hadoop administration.
Hadoop MapReduce Framework
- Traditional ways vs MapReduce way.
- Why MapReduce?
- YARN components.
- YARN architecture.
- YARN MapReduce application execution flow.
- YARN workflow.
- Anatomy of MapReduce program.
- Input splits, relations between HDFS blocks and input splits.
- MapReduce: partitioners and combiner.
- Demo of health care dataset.
- Demo of weather dataset.
Advanced Hadoop MapReduce
- Counters.
- Distributed cache.
- MR unit.
- Reduce Join.
- Custom input format.
- Sequence input format.
- XML file parsing using MapReduce.
Apache Pig
- Introduction to Apache Pig.
- MapReduce vs pig.
- Pig components and pig execution.
- Data models in Pig.
- Pig Latin programs.
- Utility and shell commands.
- Pig streaming and UDF.
- Testing pig scripts with Punit.
- Aviation use-case in PIG.
- Pig demo of healthcare dataset.
Apache Hive
- Introduction to apache hive.
- Hive vs pig.
- Hive architecture and components.
- Hive megastore.
- Limitations of Hive.
- Comparison with a traditional database.
- Hive data types and data models.
- Hive partition.
- Hive bucketing.
- Hive tables.
- Importing data.
- Querying data and managing outputs.
- Hive scripts and hive UDF.
- Retail use case in Hive.
- Hive demo on healthcare dataset.
Advanced Apache Hive and HBase
- Hive QL: joining tables and dynamic partitioning.
- Custom MapReduce scripts.
- Hive views and indexes.
- Hive query optimizers.
- Hive thrift server.
- Hive UDF.
- Introduction to NoSQL Databases and HBase.
- HBase vs RDBMS.
- HBase components.
- HBase architecture.
- HBase run modes.
- HBase configuration.
- HBase cluster deployment.
Advanced Apache HBase
- HBase data model.
- HBase shell.
- HBase client API.
- Hive data loading techniques.
- Apache zookeeper introduction.
- Zookeeper data model.
- Zookeeper service.
- HBase bulk loading.
- Getting and inserting data.
- HBase filters.
Processing Distributed Data with Apache Spark
- What is the spark?
- Spark ecosystem.
- Spark components.
- What is Scala?
- Why Scala?
- SparkContext.
- Spark RDD.
Oozie and Hadoop Project
- Oozie.
- Oozie components.
- Oozie workflow.
- Scheduling jobs with Oozie scheduler.
- Demo of Oozie workflow.
- Oozie coordinator.
- Oozie commands.
- Oozie web console.
- Oozie for MapReduce.
- Combining the flow of MapReduce jobs.
- Oozie hive.
- Hadoop project demo.
- Hadoop Talend integration.
Certification Project
- Analyses of an online bookstore.
- Airlines analysis.
Course Fee
INR 16,995
Per Month EMI
INR 5,665
Also, Check,
3. Learn About the PySpark Certification Training Course
This certification course is helpful to become a big data and spark developer. You will understand the basics of big data and will know data processing ways. The fundamental concepts are most important to adopt new skills. Learning new things while selecting data analytics courses at Edureka will be good for exposure.
Course Details
Introduction to Big Data Hadoop and Spark
- What is big data?
- Big data customer scenarios.
- Limitations and solutions of existing data analytics architecture with Uber use case.
- How Hadoop solves the big data problem?
- What is Hadoop?
- Hadoop’s key characteristics.
- Hadoop ecosystem and HDFS.
- Hadoop core components.
- Rack awareness and block replication.
- YARN and its advantage.
- Hadoop cluster and its architecture.
- Hadoop has different cluster modes.
- Big data analytics with batch and real-time processing.
- Why is spark needed?
- What is the spark?
- How spark differs from its competitors?
- Spark at eBay.
- Spark’s place in the Hadoop ecosystem.
Introduction to Python for Apache Spark
- Overview of python.
- Different applications where python is used.
- Values, variables and types.
- Expressions and operands.
- Conditional statements.
- Loops.
- Command line arguments.
- Writing to the screen.
- Python files I/O functions.
- Numbers.
- Strings and related operations.
- Lists and related operations.
- Dictionaries and related operations.
- Sets and related operations.
- Functions.
- Function parameters.
- Global variables.
- Variable scope and returning values.
- Lambda functions.
- Object-oriented concepts.
- Standard libraries.
- Modules used in Python.
- The import statements.
- Module search path.
- Package installation ways.
Deep Drive into Apache Spark Framework
- Spark components and their architecture.
- Spark deployment modes.
- Introduction to PySpark shell.
- Submitting PySpark job.
- Spark web UI.
- Understand and learn your first PySpark assignment using Jupyter Notebook.
- Data ingestion using Sqoop.
Playing with Spark RDDs
- Challenges in existing computing methods.
- Probable solution and how RDD solves the problems.
- What is RDD, its operations, actions and transformations?
- Data loading and saving through RDDs.
- Key-value pair RDDs.
- Other pair RDDs and two pair RDDs.
- RDD lineage.
- RDD persistence.
- Wordcount program using RDD concept.
- RDD partitioning and how it helps achieve parallelisation.
- Passing functions to spark.
Data Frames and Spark SQL
- Need for spark SQL.
- What is spark SQL?
- Spark SQL architecture.
- SQL context in spark SQL.
- Schema RDDs.
- User-defined functions.
- Data frames and datasets.
- JSON and parquet file formats.
- Loading data through different sources.
- Spark-hive integration.
Machine Learning using Spark MLIib
- Why machine learning?
- What is machine learning?
- Where machine learning is used.
- Face detection: USE CASE.
- Different types of machine learning techniques.
- Introduction to MLlib.
- Features of MLlib and its tools.
- Various machine learning algorithms are supported by MLlib.
Deep Dive into Spark MLlib
- Supervised learning: logistic regression, random forest, linear regression
- Unsupervised learning: K clustering
- Analysis of US election data using MLlib.
Understanding Apache Flume and Kafka
- What is Kafka?
- Need for Kafka.
- Core concepts of Kafka.
- Kafka architecture.
- Where is Kafka used?
- Understanding the components of the Kafka cluster.
- Configuring Kafka cluster.
- Kafka producer and consumer java API.
- Need of Apache Flume.
- What is Apache Flume?
- Basic Flume architecture.
- Flume source.
- Flume sinks.
- Flume channels.
- Flume configuration.
- Integrating Apache Flume and Kafka.
Apache Spark Streaming- Processing Multiple Batches
- Drawbacks in existing computing methods.
- Why streaming is necessary?
- What is spark steaming?
- Spark streaming features.
- Spark streaming workflow.
- How Uber uses streaming data?
- Streaming context and DStreams.
- Transformations on DStreams.
- Describe windowed operators and their usefulness.
- Important windowed operators.
- Window, slice and reduce by window operators.
- Stateful operators.
Apache Spark Streaming: Data Sources
- Apache spark data sources.
- Streaming data source overview.
- Apache flume
- Kafka data sources.
- Using Kafka direct data source.
Implementing an End-to-End Project
- Project One is Finance.
- Project Two is media and entertainment.
Spark GraphX (Self-paced)
- Introduction to Spark GraphX.
- Information about a graph.
- GraphX basic APIs and operations.
- Spark GraphX algorithm.
Course Fee
INR 18,695
Per Month EMI
INR 6,232
4. Learn About Apache Spark and Scala Certification Training Course
This course is always will be helpful if you want to learn a particular skill or segment. They have small courses as well as big courses. Understanding segments will be good for your future growth. You will learn everything after joining data analytics courses at Edureka. Everything you will be doing can be an added advantage for you. You can learn everything in good and possible ways to think about a well future.
Course Details
Introduction to Big Data Hadoop and Spark
- What is big data?
- Big data customer scenarios.
- How Hadoop solves the big data problem?
- What is Hadoop?
- Hadoop’s key characteristics.
- Hadoop ecosystem and HDFS.
- Hadoop core components.
- Block replication and rack awareness.
- YARN and its advantage.
- Hadoop cluster and its architecture.
- Hadoop has different cluster modes.
- Hadoop terminal commands.
- Why is Spark needed?
- What is Spark?
- How Spark differs from other frameworks?
- Spark at Yahoo.
Introduction to Scala for Apache Spark
- What is Scala?
- Why Scala for spark?
- Scala in other frameworks.
- Introduction to Scala REPL.
- Basic Scala operations.
- Variable types in Scala.
- Foreach loop, procedures and functions.
- Collections in Scala-Arrey.
- Map, Array buffer, lists and Tuples.
Functional Programming and OOPs Concepts in Scala
- Functional programming.
- Higher-order functions.
- Anonymous functions.
- Class in Scala.
- Setters and getters.
- Custom getters and setters.
- Properties with only getters.
- Primary and auxiliary constructor.
- Singletons.
- Extending a class.
- Overriding methods.
- Traits as interfaces and layered traits.
Deep Drive into Apache Spark Framework
- Spark’s place in the Hadoop ecosystem.
- Spark components and their architecture.
- Spark deployment models.
- Introduction to spark-shell.
- Writing your first spark job using SBT.
- Submitting spark job.
- Spark web UI.
- Data ingestion using Sqoop.
Playing with Spark RDDs
- Challenges in existing computing methods.
- Ways to solves RDDs problem and added solutions.
- What are RDD, operations, actions and transformations?
- Data loading and saving through RDDs.
- Key-value pair RDDs.
- Other pair RDDs, two pair RDDs.
- RDD lineage.
- RDD persistence.
- Wordcount program using RDD concept.
- RDD partitioning and how it helps to achieve parallelisation.
- Passing functions to spark.
Data Frames and Spark SQL
- What is spark SQL?
- Need for spark SQL.
- Spark SQL Architecture.
- SQL context in spark SQL.
- User-defined functions.
- Datasets and frames.
- Interoperating with RDDs.
- JSON and parquet file formats.
- Loading data through different sources.
- Spark -hive integration.
Machine Learning using spark MLlib
- What is machine learning?
- Why machine learning?
- Where is machine learning used?
- Use case: Face detection.
- Different types of machine learning techniques.
- Introduction to MLlib.
- Features of MLlib tools and MLlib.
- Various ML algorithms are supported by MLlib.
Deep Drive into Spark MLlib
- Supervised learning.
- Unsupervised learning.
- Analyse US election data using MLlib.
Understanding Apache Flume and Kafka
- What is Kafka?
- Need for Kafka.
- Core concepts of Kafka.
- Kafka architecture.
- Where is Kafka used?
- Understanding the components of the Kafka cluster.
- Configuring Kafka cluster.
- Kafka producer and consumer java API.
- Need of Apache Flume.
- What is Apache Flume?
- Basic Flume architecture.
- Flume source.
- Flume sinks.
- Flume channels.
- Flume configuration.
- Integrating Apache Flume and Kafka.
Apache Spark Streaming- Processing Multiple Batches
- Drawbacks in existing computing methods.
- Why streaming is necessary?
- What is spark steaming?
- Spark streaming features.
- Spark streaming workflow.
- How Uber uses streaming data?
- Streaming context and DStreams.
- Transformations on DStreams.
- Describe windowed operators and their usefulness.
- Important windowed operators.
- Window, slice and reduce by window operators.
- Stateful operators.
Apache Spark Streaming: Data Sources
- Apache spark data sources.
- Streaming data source overview.
- Apache flume and kafka data sources.
- Using Kafka direct data source.
- Perform Twitter sentimental analysis using spark streaming.
Course Fee
INR 18,695
Per Month EMI
INR 6,232
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5. Learn About Apache Kafka Certification Training Course
Apache Kafka certification training helps you with the ways to use it. The training process always creates a strong integration process to gather experience about the course. You will slowly know the training objectives and demands in the market. If you are looking for particular data analytics courses at Edureka. You might get benefits.
Course Details
- Introduction to big data and Apache Kafka.
- Kafka producer.
- Kafka consumer.
- Kafka internals.
- Kafka cluster architecture and administering Kafka.
- Kafka monitoring and Kafka connect.
- Kafka steam processsing.
- Integration of Kafka with Hadoop, spark and Strom.
- Integration of Kafka with Cassandra, Talend.
- Kafka in-class project.
- Certification project.
Course Fee
INR 15,125
Per Month EMI
INR 5,042
6. Learn About Splunk Certification Traning: Power User and Admin
This certification course is always helpful to understand the Splunk power user and admin process. Within the course end, you will understand the roles and responsibilities of the online training process. Everything will be good to understand the different knowledge objectives and their visualization process. Understanding particular data analytics courses at Edureka will be helpful if you want to learn any specific course.
Course Details
- Introduction to machine learning and Splunk basics.
- User management and Splunk configuration files.
- Data infestation, reporting commands and Splunk search.
- Knowing objects I.
- Knowing objects II.
- Splunk alerts, dashboards, reports and visualisation.
- Splunk clustering techniques.
- Case studies and project discussion.
Course Fee
INR 15,125
Per Month EMI
INR 5,042
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7. Learn About Azure Data Engineer Associate Certification Course
This training is all about transforming and loading data and extracting from several sources. Unstructured and structured data can be found on any site. While understanding the fundamentals of Azure, you can get one free video that is only available if you enrol in data analytics courses at Edureka.
Course Details
- Introduction to Azure data engineering.
- Storing data in Azure.
- Azure data factory part I.
- Azure data factory Part II.
- Azure synapse analytics part-I.
- Azure synapse analytics part II.
- Work with data warehouses using Azure synapse analytics part-A.
- Work with data warehouses using Azure synapse analytics part B.
- Optimising data queries in Azure.
- Managing workloads in Azure synapse analytics.
- Deep dive into Azure data bricks.
Course Fee
INR 16, 995
Per Month EMI
INR 5,665
8. Learn About Big Data Hadoop Administration Certification Training
This course mostly focuses on the installation, and configuration to load balance. There are few institutions available that provide particular skills training and data analytics courses at Edureka are one of them. You can ask any questions to the administration department.
Course Details
- Understanding big data and Hadoop.
- Hadoop cluster and its architecture.
- Hadoop cluster working and setup.
- Hadoop cluster maintenance and administration.
- Computational frameworks. Scheduling, and managing resources.
- Hadoop 2. X cluster: management and planning.
- Hadoop cluster and security monitoring.
- Cloudera Hadoop 2. X and their features. (self-paced)
- Pig, working and hive installation. (self-paced)
- HBase, Zookeeper installation and working. (self-paced)
- Understanding Oozie. (self-paced)
- Data ingestion using Sqoop and Flume. (self-paced)
Course Fee
INR 15,125
Per Month EMI
INR 5,042
FAQs (Frequently Asked Questions)
Q 1. After joining data analytics courses at Edureka if I miss any class how will I catch up?
Every course has its recordings. In every course section, you can get recorded sessions. If you missed the recorded session then you can talk to them and join another live batch at your convenient time. There are high-quality standards to conduct quality training sessions. Never think that you are left alone. If you feel like that you can talk to them. They always prioritize you, that’s their main motive. Every student is valuable to them.
Q 2. What If I require course material in the future? What I shall do?
You will get full access to the learning materials to gather some good learnings in the future. Even you will get 60 days of could access to understand real-life problems. Before class starts, you will get access to the learning materials. You can read Pdfs to be prepared for future development. You have to understand the complete process to focus on future possibilities. Every student will require course material in the future. They always give access to understanding more about the course in the best way possible. While you gather experience practically then you will know the actual use of the skills. You can focus on learning and solving queries for future benefits.
Q 3. Online or Offline which course will be better?
You will get to understand the process of real-life case studies. Taking data analytics courses at Edureka will be good. At every class end, you will submit one assignment. You will get lifetime access to class materials and available other benefits. The team will give 24 X 7 guidance. After completing the final course, you can become a big data expert. You will get to join a professional forum to understand trendy news from industry experts.
Conclusion
Most case studies are based on real-life problems. You can showcase everything you did while taking data analytics courses at Edureka. By installing and configuring components in the ecosystem, you can create your awareness to learn about the course. Learning big data can be good for the real world. After learning about their course, you can work as a system administrator, database administrator, or infrastructure administrator. If you learn the basics of everything you will be prepared to face any challenges.
