Python Programming & Data Science Foundations by Harsh Goyal

Python has become one of the most important programming languages in today’s technology world. From data science and analytics to automation and application development, Python is used everywhere. This online Python Programming and Data Science Foundations course by Harsh Goyal is specially designed for beginners and aspiring data analysts / data scientists who want to start their journey in coding and data-driven problem solving.

The course begins with Python fundamentals and gradually introduces data analysis, NumPy, Pandas, SQL basics, and data visualization, ensuring that students build a strong, practical foundation step-by-step. Whether you are a student, fresher, working professional, or someone shifting careers into the data field, this course provides a guided pathway to develop the right skills with clarity and confidence.

Course Overview

This program focuses on hands-on learning with real examples and problem-solving exercises. Concepts are explained in simple language so that even absolute beginners can follow comfortably. By the end of the course, learners will not only understand Python but will also be able to analyse data, handle datasets, and work with popular data science libraries.

The course is ideal for:

• Students beginning their coding journey

• Fresh graduates preparing for technical roles

• Professionals entering data analytics / data science

• Learners wanting structured Python learning

• Anyone curious about working with data

What Students Will Learn

Students will develop strong fundamentals in:

• Python Basics

  • Syntax and writing your first programs

  • Data types, variables, operators

  • Input / output

  • Working with real-world examples

• Control Flow

  • Conditional statements

  • Loops and iterations

  • Logical problem solving

• Functions

  • Function design and reuse

  • Parameters, returns & modular coding

• Object-Oriented Programming (OOP)

  • Classes, objects & methods

  • Real-life OOP examples

• File Handling

  • Reading and writing files

  • Working with data files

• NumPy

  • Arrays and numerical computing

  • Fast data operations

• Pandas

  • DataFrames & dataset handling

  • Cleaning, transforming & analysing data

• Data Analysis Skills

  • Discovering patterns in data

  • Practical case-based exercises

• Data Visualisation

  • Charts & graphs

  • Visual storytelling concepts

• SQL & Databases (DBMS basics)

  • Understanding databases

  • Querying data using SQL

  • Retrieving and filtering results

• Automation Basics

  • Writing scripts to automate simple tasks

• Problem Solving Mindset

  • Logical thinking

  • Step-by-step coding approach

Optional exposure to R programming may also be included to introduce multi-tool awareness for data science environments.

Teaching Method

This is a live online course, where learning is practical and interactive. Sessions include:

• Concept explanation with clarity

• Coding demonstrations

• Hands-on practice

• Guided exercises

• Simple dataset projects

• Continuous doubt clarification

Students are encouraged to build confidence by writing real code during sessions, not just watching.

Why Learn with Tutor Harsh Goyal

Tutor Harsh Goyal maintains a beginner-friendly, structured teaching style that focuses on understanding rather than memorisation. Each topic is taught with relatable examples so students develop both technical knowledge and logical thinking. The aim is to help learners feel comfortable with Python and data tools, even if they are starting from scratch.

Benefits & Outcomes

After completing this course, learners can:

• Write Python programs confidently

• Analyse and manage data using Pandas & NumPy

• Create visualisations with Matplotlib

• Understand SQL database queries

• Apply data science logic to real problems

• Strengthen coding fundamentals for future learning

• Build a pathway toward careers such as Data Analyst / Data Scientist / Python Developer

This course provides a solid starting point for anyone entering programming and data science with structured guidance and practical exposure.