I am a passionate and experienced Data Engineer with a strong background in Python scala java js htmlprogramming and aws.

I am an experienced Data Engineer with a strong proficiency in Python programming, which I use extensively for data manipulation, analysis, and developing data pipelines. My background includes significant work in data management, ETL processes, and data modeling. In my current role at Adthena in London, I use Python daily to manage various BI applications, generating reports that help in decision-making. I also collaborate with the data science team to deploy machine learning models, leveraging Python to facilitate data-driven insights. I have hands-on experience with AWS services like S3, Redshift, Glue, EMR, and Lambda, integrating them with Python to build efficient data pipelines. My educational background includes a Master's degree in Big Data and Business Intelligence from the University of Greenwich and a Bachelor's degree in Computer Engineering from Gujarat Technological University. Briefly Explain How You Will Teach My teaching approach is practical and student-focused, especially when it comes to Python programming. Here’s how I plan to teach: Assessing Skills and Goals: I’ll start by understanding the student's current Python skills and what they hope to achieve. This helps me tailor the lessons to their specific needs. Creating a Structured Curriculum: I’ll design a curriculum that starts with the basics of Python and progresses to more advanced topics. We’ll cover Python syntax, data structures, and important libraries like pandas, NumPy, and matplotlib. Interactive Learning: Each session will be interactive, with lots of coding exercises and real-world problems to solve. This hands-on approach helps reinforce what we’ve covered. Using Modern Tools: I’ll introduce students to tools and libraries that enhance Python programming, such as Jupyter notebooks for interactive coding, and libraries for data processing and visualization. Project-Based Learning: We’ll work on real-world projects together. This could involve data analysis, ETL processes, or even building simple machine learning models. These projects make learning practical and engaging. Regular Assignments and Feedback: To ensure continuous improvement, I’ll assign regular homework and projects, providing detailed feedback. This helps students see where they can improve and what they’re doing well.