Data Engineering Course is one of the most in-demand career options in today's world. Data Engineering is the process of turning unprocessed data into useful knowledge.
With the introduction and accessibility of data in our daily lives, it is a crucial procedure for businesses that wish to make data-driven decisions, and its significance is growing.
Course Objective
- Become a master of Microsoft Excel.
- Gain proficiency in data analysis by learning statistics.
- Learn the art of Structured Query Language (SQL) which helps you to handle structured data.
- Boost your confidence by learning basic programming and API.
- Scale up your knowledge skill with the concept of big data.
- Get in-depth insights into big data management.
- Keep yourself workplace-ready by working on a big data analytics project.
- Learn the skills of data warehousing and data lake and stay one step ahead.
Prerequisites
Anyone can join data engineering classes after completing the 12th grade. It is good to have some basic knowledge, but it’s not mandatory for enrollment.
Why Data Engineering Certification?
- Get Hired Faster: Certification will validate your skills to employers and increase the chances of getting hired.
- Land Better Jobs: Industry-recognized certification helps you to get better jobs with a high pay scale.
- Boost Your Career: Become a certified professional per the industry demand and open doors to new opportunities.
- Stay Relevant: Data engineering course certifications are equipped with the latest tools and trends that the industry currently needs in data engineers.
- Bridge the Gap: Certification allows you to work on live projects and fill the gaps between your studies and real-world jobs.
Why do Data Engineering Training from ICA Edu Skills?
The experience and expertise of 25 Years will equip students with industry-relevant skills and knowledge. Explore What the ICA Data Engineering course will offer:
NSDC Certified Training IOA UK Certified Real-Life Projects Group Discussion Mock Interviews 100% Job AssistanceSkills Covered
| Data Analysis in Excel | Data Visualization | Hypotheses Testing |
| SQL Database | API – Hands-on Experience | Data Structure and Algorithm |
| Hadoop Framework | Apache Cassandra and No SQL | Data Management |
| Big Data Analytics | Real-Time Data Processing | Data Injection |
| Data Transformation | Advanced Cloud Data warehouses | Data Protection |
Tools Covered
Industry Projects
The Data Engineering Course will give you hands-on practical experience by furnishing you with industry projects. These skills will make you ready to deal with workplace challenges.
Projects include Recommendation Engine, Chat Bot, Marketing Analytics, Retail Analytics, Finance Analytics, HR Analytics, Health Care Analytics, Sports Analytics etc.
Who Should Enroll in the Data Engineering Course?
- Want to switch careers?: Anyone with a technical background and looking to switch careers, can enroll in a data engineering course.
- Just graduated?: Have you completed your graduation recently and are interested in becoming a data engineer? This course perfectly fits your career aspiration and helps you to follow your passion for data.
- Already in tech?: Already serving in the technical field, the data engineering course boosts your skills and helps you become a data engineering pro!
What You Will Master in the Certificate Course On Data Engineering
- Microsoft Excel: Achieve Excel mastery by learning basic Excel and advanced Excel formulas that supercharge your data visualization and analysis skills.
- Statistics: Statistics concepts like charts, graphs, Hypothesis Testing, their types, and errors will accelerate your career path in the right direction with the right skill sets.
- SQL: From installing to handling basic commands on SQL to the database example, everything will be covered in the data engineering class.
- Basic Programming and API: The data engineering class will train you in basic programming, data management, and practical training on handling APIs.
- Big Data: The data engineering course will focus on the big data framework, concepts of Hadoop, SPARK, SCALA, HDFS, data structure, and algorithms.
- Big Data Management: Certification will set your skills on Apache Cassandra and No SQL, Relational and non-relational databases.
- Big Data Analytics Project: The course will set you apart from others by providing you with practical knowledge of Hive, H-Base, YARN, APACHE AMBARI, KAFKA, and more.
- Cloud Data Warehousing and Data Lake: Gain expertise with the course on cloud data warehouses, data lakes using SPRAK, data injection, and more by working practically on projects.
Data Engineering Certification
Career Opportunities After Data Engineering Certification
- Data Engineer
- Big Data Engineer
- Cloud Data Engineer
- Data Warehouse Engineer
- Data Integration Specialist
- ETL Developer
- Data Architect
- Data Governance and Security Specialist
- Data Consultant
- Microsoft Excel
- Statistics
- SQL ( Database Management System )
- Basis of Programing and API
- Big Data
- Big Data Management
- Big Data Analytics Project
- Cloud Data Warehousing and Data Lake 1
- Cloud Data Warehousing and Data Lake 2
6 Hours
4 Lecture
Lecture 1 : Basic of Excel
Lecture 2 : Visualization in Excel
Lecture 3 : Data Analysis in Excel
Lecture 4 : Formula, Loops
12 Hours
16 Lecture
Lecture 1 : What is Statistics
Lecture 2 : Types of Statistics
Lecture 3 : Graph
Lecture 4 : Charts
Lecture 5 : Distribution
Lecture 6 : Standard Deviation
Lecture 7 : Variance
Lecture 8 : Measure of Dispersion
Lecture 9 : Sampling Probability Theorems
Lecture 10 : Type of Probability
Lecture 11 : Distribution
Lecture 12 : Z score
Lecture 13 : Hypotheses Testing
Lecture 14 : Central Limit Thermos
Lecture 15 : Types of Hypothesis Testing
Lecture 16 : Types of errors in Hypotheses Testing
12 Hours
7 Lecture
Lecture 1 : Install My SQL Work Bench
Lecture 2 : Introduction to SQL
Lecture 3 : Basic to SQL
Lecture 4 : Basic command in SQL
Lecture 5 : SQL Data Base
Lecture 6 : SQL references
Lecture 7 : Data Base Examples
10 Hours
2 Lecture
Lecture 1 : Introduction to Data Management
Lecture 2 : Introduction to API – Hands on
15 Hours
9 Lecture
Lecture 1 : Introduction to BIG Data
Lecture 2 : Framework of Big Data
Lecture 3 : Data Structure and Algorithm
Lecture 4 : Introduction to Distributed and Parlel Computing in Big Data
Lecture 5 : Introduction to Hadoop
Lecture 6 : Hadoop Framework
Lecture 7 : Basis and Advance HDFS Concepts
Lecture 8 : Introduction and handson map reduce
Lecture 9 : Advance concepts in SPARK AND SCALA
15 Hours
5 Lecture
Lecture 1 : Introduction to Relational and Non relational data bases
Lecture 2 : Introduction to Apach Cassandra and No SQL
Lecture 3 : Data Management in Relational Data Bases
Lecture 4 : Hands on No Sql
Lecture 5 : Introduction and Hands on Mongo DB
100 Hours
10 Lecture
Lecture 1 : MAP REDUCE
Lecture 2 : SPARK
Lecture 3 : SCALA
Lecture 4 : HIVE
Lecture 5 : H- Base
Lecture 6 : YARN
Lecture 7 : APECHE AMBARI
Lecture 8 : KAFKA
Lecture 9 : NO Sql
Lecture 10 : NO Sql
50 Hours
8 Lecture
Lecture 1 : Advance Cloud Data Ware Houses
Lecture 2 : Advance ETL using HIVE and other tools
Lecture 3 : Building an Data Lake – Hands on Project
Lecture 4 : Building Data Lake using SPRAK
Lecture 5 : Data Injection using SCOOP
Lecture 6 : KAFKA
Lecture 7 : NO Sql
Lecture 8 : Mogo DB
50 Hours
5 Lecture
Lecture 1 : Advance Cloud Data Ware Houses
Lecture 2 : Advance ETL using HIVE and other tools
Lecture 3 : Building an Data Lake – Hands on Project
Lecture 4 : Building Data Lake using SPRAK
Lecture 5 : Data Injection using SCOOP
