Abhishek Gupta - Data Engineer With 4.2 Years In IT Industry

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Data Analytics classes

4

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Python Training classes

1

Teaching Experience in detail in Python Training classes

I have over 1 year of experience teaching and mentoring students, data analysts, and software engineers in Apache Spark using PySpark. My training is designed to bridge the gap between basic Python scripting and large-scale, distributed Big Data processing. Core topics covered in my sessions include: PySpark Architecture: SparkSession, cluster internals, Driver and Executors, lazy evaluation, DAG execution, and DAG visualization. DataFrame & Dataset API: Schema definitions (StructType, StructField), reading/writing multi-format data (CSV, JSON, Parquet), filtering, transformations, and actions. Data Transformations & Aggregations: Grouping, sorting, joins, built-in functions (pyspark.sql.functions), and User Defined Functions (UDFs). Advanced PySpark: Window functions, partitioned tables, caching/persistence strategies, and understanding data shuffling. Spark SQL: Running direct SQL queries on PySpark DataFrames and temp views. Performance Tuning Basics: Repartitioning vs. coalescing, broadcast joins, and handling skewed data. My sessions prioritize 100% hands-on learning using real-world datasets in environments like Databricks . I provide practical pipeline building exercises, interview preparation sets, and real-time debugging guidance to make students job-ready.

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in SQL Programming Training

1

Teaching Experience in detail in SQL Programming Training

I have 1 year of experience teaching and mentoring students, fresh graduates, and professionals in SQL Programming and Relational Database Management Systems (RDBMS). My training approach focuses on bridging the gap between database theory and writing clean, optimized queries for real-world scenarios. Topics I cover in depth include: SQL Fundamentals: Database design, tables, constraints, and core commands (DDL, DML, DQL, DCL). Querying & Filtering: SELECT, WHERE, ORDER BY, GROUP BY, HAVING, and built-in aggregate and scalar functions. Relational Data & Joins: Inner joins, left/right outer joins, full joins, and cross joins. Advanced SQL Concepts: Subqueries, nested queries, Common Table Expressions (CTEs), and window functions (ROW_NUMBER, RANK, DENSE_RANK). Data Integrity & Management: Primary keys, foreign keys, views, transactions, and basic query optimization. My sessions are 100% hands-on, conducted with tools like Databricks Community Edition, which is free of cost. Each session is accompanied by real-time schema problem sets, interview-focused query challenges, and regular doubt-clearing sessions to ensure students become confident in writing database queries independently.