Abhishek Payezhi Chegattil - Data Expert: 9+ years Python, SQL, Kubernetes

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Python Training classes

10

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Kubernetes

3

Teaching Experience in detail in Kubernetes

Kubernetes can feel overwhelming at first, but it becomes very powerful once the core concepts click. Over the past years, I have worked on enterprise-grade Kubernetes solutions for European clients, designing and operating multi-cloud platforms that run across providers like AWS, Azure, and on-prem environments. This experience includes setting up production clusters, managing workloads at scale, and integrating Kubernetes with CI/CD, observability, security, and data platforms. In sessions with you, the focus will be practical and hands-on. We will start with the essentials: Pods, Deployments, Services, ConfigMaps/Secrets, and basic networking—so you understand how applications are actually run and exposed in a cluster. From there, we will move into more advanced and real-world topics such as namespaces and multi-tenant setups, Ingress and API gateways, Helm/Kustomize, resource limits, autoscaling, and troubleshooting with logs and metrics.

Class Location

Online class via Zoom

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Tutor's Home

Years of Experience in Web Development Classes

3

Teaching Experience in detail in Web Development Classes

This course focuses on building a strong, practical foundation in web development using Python, HTML, and CSS. You will learn how the web actually works: how the browser sends requests, how the server responds, and how Python can power dynamic web pages. By manually working with HTML structure and CSS styling, you will understand layout, design, and responsiveness before jumping into more complex frontend frameworks. The sessions are especially recommended if you already know Python and now want to bring your skills to the web. We will start with core web concepts (HTTP, routing, forms, templates) and build small but complete applications step by step. From there, we will introduce Python web frameworks such as Flask, Django, or FastAPI, so you can see different ways to structure backend logic, handle APIs, manage templates, and work with databases. By the end of the course, you will be comfortable building and deploying basic web applications, creating clean HTML/CSS interfaces, and exposing REST APIs in Python. This will give you the right foundation to move confidently into mainstream frontend and fullstack ecosystems such as React and Node.js, because you will already understand the underlying principles of the web and server-side development.

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in SQL Programming Training

3

Teaching Experience in detail in SQL Programming Training

Whether you are just starting with SQL or already comfortable with queries and want to level up, this course will take you from fundamentals to advanced, production-ready skills used in real data engineering environments. We begin with SQL essentials: selecting, filtering, joins, aggregations, and subqueries—ensuring you have a solid foundation. From there, we move into more advanced topics that separate beginners from professionals: window functions, CTEs (Common Table Expressions), query optimization, indexing strategies, and understanding execution plans. For those working in modern data platforms, we will dive deep into concepts critical to large-scale data warehousing and analytics: table partitioning, bucketing and clustering, data modeling for OLAP (Online Analytical Processing), and designing efficient schemas for analytics workloads. You will learn how these techniques dramatically improve query performance and reduce costs in cloud environments. The hands-on part is where theory meets practice. We will work with industry-standard tools like Trino (distributed SQL engine) or Databricks (Apache Spark-based analytics platform), running real queries on large datasets, optimizing performance, and exploring how SQL powers business intelligence and data science pipelines in production systems. By the end, you will not only write SQL confidently but also understand how to design, optimize, and troubleshoot data warehouses and analytical workloads at scale—skills directly applicable to roles in data engineering, analytics, and business intelligence.