What is Certified Data Engineer?
Datamites Team
Certified Data Engineer, recognized globally by IABAC, is available through DataMites, a prestigious Platinum Partner in data engineer courses. This comprehensive 6-month course not only equips you with essential skills but also provides valuable real-world experience through data engineer internships and live projects, ensuring you're well-prepared for the vital field of data engineering.
In the Certified Data Engineer Training, you'll learn important skills for jobs that handle data. There are 8 courses that cover everything you need to know. You'll get really good at what you need to do in data engineering roles because of this focused training.
- Data Engineer Foundation
- Python Foundation
- Statistics Essentials
- Data Engineering Associate
- Data Engineering - AWS & Azure Cloud
- Version Control with Git
- Database: SQL and MongoDB
- Big Data Foundation
Refer these below articles:
- Guide to Data Engineer Career
- What would be the Data Engineer Course Fee in India?
- Navigating the Distinctive Paths of Data Architects and Data Engineers
Let's take a closer look at the Certified Data Engineer Course:
1. Data Engineer Foundation - This course lays the groundwork for becoming a data engineer, teaching basic concepts and skills needed in the field.
What Will Be Covered - Data Engineering Introduction, Data Sources And Data Import, Data Processing, And Data Engineering Project.
Prerequisites - None
Learning Hours - 20 Hours
2. Python Foundation - Learn the fundamentals of Python programming, essential for data engineering tasks like data manipulation and analysis.
What Will Be Covered - Python Basics, Python Control Statements, Python Data Structures, Python Functions, Python Numpy Package, And Python Pandas Package.
Prerequisites - None
Learning Hours - 40 Hours
3. Statistics Essentials - Understand key statistical concepts necessary for interpreting data accurately and making informed decisions in data engineering projects.
What Will Be Covered - Overview Of Statistics, Harnessing Data, Exploratory Data Analysis, Hypothesis Testing, And Correlation And Regression.
Prerequisites - None
Learning Hours - 20 Hours
4. Data Engineering Associate - Dive deeper into data engineering techniques and tools, gaining practical knowledge to handle real-world data processing tasks.
What Will Be Covered - Data Engineering Introduction, Data Warehouse Foundation, Data Sources And Data Import, Data Processing Docker And Kubernetes Foundation, Data Orchestration With Apache Airflow, And Data Engineering Project.
Prerequisites - None
Learning Hours - 20 Hours
5. Data Engineering On AWS & Azure Cloud - Explore how to utilize cloud platforms like AWS and Azure for data engineering tasks, including data storage, processing, and analysis.
What Will Be Covered - Aws Data Services Introduction, Data Ingestion Using Aws Lamdba, Data Pipeline With Aws Kinesis, Data Warehouse With Aws Redshift, Data Pipeline With Azure Synapse, Storage In Azure, Azure Data Factory, And Data Engineering Project With Azure/Aws.
Prerequisites - None
Learning Hours - 40 Hours
6. Version Control With Git - Learn how to effectively manage and track changes to your code and data engineering projects using Git, a popular version control system.
What Will Be Covered - Git Introduction, Git Repository And Github, Commits, Pull, Fetch, And Push, Tagging, Branching, And Merging, Undoing Changes, And Git With Github And Bitbucket.
Prerequisites - None
Learning Hours - 10 Hours
7. Database: SQL And MongoDB - Master SQL for relational databases and MongoDB for NoSQL databases, crucial for storing and retrieving data efficiently in data engineering projects.
What Will Be Covered - Database Introduction, Sql Basics, Data Types And Constraints, Databases And Tables (Mysql), Sql Joins, Sql Commands And Clauses, And Documenst DB/No-SQL DB.
Prerequisites - None
Learning Hours - 15 Hours
8. Big Data Foundation - Gain an understanding of big data concepts and technologies like Hadoop and Spark, essential for handling large-scale data processing tasks effectively.
What Will Be Covered - Big Data Introduction, Hdfs And Map Reduce, Pyspark Foundation, Spark Sql And Hadoop Hive, Machine Learning With Spark Ml, And Kafka And Spark.
Prerequisites - Python Foundation
Learning Hours - 10 Hours
With the global market for big data and data engineering services expected to reach $87.37 billion by the year 2025, and over 180,000+ data engineer job postings on LinkedIn worldwide, the demand for skilled professionals in this field is evident. Moreover, data engineers command impressive salaries;
- The average Data Engineer Salary in United States is $127,786 per year. - Indeed.
- The average salary for a data engineer is £56,188 per year in London - Glassdoor.
- The average salary for a Data Engineer in India is ₹10,00,000 per year. - Glassdoor.
Considering the high demand and lucrative salaries, now is the perfect time to pursue a career in data engineering. DataMites Certified Data Engineer Program is a career-oriented program designed to upskill individuals in this field. With a curriculum regularly updated to meet industry standards and 220 hours of learning, you can become a certified data engineer in just six months.
Join DataMites CDE course today and embark on an exciting journey towards a rewarding career in data engineering.
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