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Data Engineering with Python

  • 24/7 Support
  • 4 Months
  • 120 Sessions

Course Description

Unleash the full potential of Python in the world of data engineering with our comprehensive course designed for aspiring data engineers, data scientists, and professionals seeking to harness the power of Python for efficient data processing and management. This hands-on program equips participants with the skills to design, build, and maintain robust data pipelines using Python, empowering them to handle large-scale data processing tasks effectively.

One to One personalized training Schedule for Data Engineering with Python

EkasCloud provides flexible training to all it's student. Here is our training schedule. Incase you find these timings difficult, please let us know. We will try to arrange appropriate timings based on your Convenience.

26-02-2024 Monday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session
28-02-2024 Wednesday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session
01-03-2024 Friday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session
02-03-2024 Saturday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session

Course Detail

Unleash the full potential of Python in the world of data engineering with our comprehensive course designed for aspiring data engineers, data scientists, and professionals seeking to harness the power of Python for efficient data processing and management. This hands-on program equips participants with the skills to design, build, and maintain robust data pipelines using Python, empowering them to handle large-scale data processing tasks effectively.

You will learn

  1. Introduction to Data Engineering:

    • Understand the role of data engineering in the data lifecycle.
    • Explore the key concepts, challenges, and best practices in data engineering.
  2. Python Fundamentals for Data Engineering:

    • Refresh and expand your Python skills, emphasizing features relevant to data engineering tasks.
    • Learn about data structures, libraries (such as NumPy and Pandas), and Pythonic coding practices for efficient data manipulation.
  3. Data Processing with PySpark:

    • Delve into PySpark, the Python library for Apache Spark, for distributed data processing.
    • Learn to manipulate and transform large datasets using PySpark's resilient distributed datasets (RDDs) and DataFrames.
  4. Working with Big Data Technologies:

    • Explore popular big data technologies such as Hadoop and Apache Kafka, and understand how to integrate Python into these ecosystems.
    • Implement Python scripts to process and analyze data stored in distributed file systems.
  5. Building ETL Pipelines:

    • Master the art of Extract, Transform, Load (ETL) processes using Python.
    • Design and implement ETL pipelines to ingest, clean, and transform data from various sources.
  6. Data Modeling and Storage:

    • Explore data modeling concepts and databases commonly used in data engineering.
    • Implement Python scripts to interact with relational and NoSQL databases for effective data storage and retrieval.
  7. Orchestrating Workflows with Apache Airflow:

    • Learn to use Apache Airflow to orchestrate complex data workflows.
    • Develop and schedule data pipelines efficiently using Python-based DAGs (Directed Acyclic Graphs).
  8. Data Quality and Testing:

    • Understand the importance of data quality in data engineering.
    • Implement testing strategies and best practices for ensuring data accuracy and reliability.
  9. Version Control and Collaboration:

    • Integrate data engineering projects with version control systems, such as Git.
    • Collaborate effectively with team members using Python and version control practices.
  10. Real-world Applications and Case Studies:

    • Apply your knowledge to real-world scenarios through hands-on projects and case studies.
    • Gain insights into industry best practices and emerging trends in data engineering.

By the end of this course, participants will be equipped with the skills and tools needed to excel in the dynamic field of data engineering with Python. Whether you're a beginner looking to enter the field or an experienced data professional seeking to enhance your Python capabilities, this course provides a practical and in-depth exploration of data engineering principles and practices.

 We check your knowledge before we start the session.

 We build foundational topics first and core topics next.

 Theory classes with a real-time case study.

 Demo on every topic.

 Mock exam on every topic you understand.

 Exam Preparation

 Interview Preparation

Data Engineering with Python Syllabus


4 Months Course 50% Theory 50% Lab Daily Home work Real time Projects

Topics Covered

  • Introduction to Data engineering
  • Python fundamentals for data engineering
  • orking with data in python
  • Introduction to Database
  • Building data pipelines with apache airflow
  • Big data technologies with python
  • Data serialization and formats
  • Real world project building an end to end pipeline
  • Version control and collaboration in data engineering
  • Best practices and optimization techniques

Instructor

Huzefa Mohammed

Huzefa has a Bachelor’s degree in Engineering.He is based out of South India and has trained more than 9000 students in the last fifteen years on various technologies starting from Networking to Cloud and is deeply passionate about their success.

Huzefa is a AWS SA PRO /AWS Security / Azure Expert & CCSP certified

 

Frequently asked question

Q: What if I miss a class?
A: We will stop the course for you because it is one-to-one or one-to-two students only.

Q: Will I get placement assistance?
A: Yes. You will get it once you are Certified.

Q: What if I have queries after I complete this course?
A: You can check our blogs or send your queries through email, social media like Facebook, Linkedin, Instagram, Twitter, and Youtube.

Q: How soon after signing up will I get access to the course?
A: Once you join the course. our Counselor Manager will book a slot with our trainer based on mutually available timings.

Q: Is the course material accessible to the students even after the course training is over?
A: Yes, you can access our course material. Not only material, but you can also watch short and sweet videos from our Youtube Channel.

Q: What is the average salary of a Python professional?
A: $100,000


Data Engineering with Python Fees