Pranav Saluja

Learn Coding the Right Way – Deep Concepts with Varied Approaches for Effective Learning

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Pranav conducting a lesson
Pranav conducting a lesson
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Coding learning materials by Pranav

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Pranav Saluja

Bachelors degree

/ 55 min

About your coding tutor - Pranav

I’m Pranav Saluja, a Computer Science tutor passionate about helping students build strong fundamentals and real-world problem-solving skills. I specialize in teaching Java, Python, Data Structures & Algorithms, and the fundamentals of Artificial Intelligence. With hands-on teaching experience, I focus on making complex concepts simple, intuitive, and easy to apply. My teaching style is highly structured and student-centric. Instead of just explaining theory, I emphasize deep understanding through clear explanations, practical examples, and guided problem-solving. I believe that learning happens best when students actively think, make mistakes, and improve with the right guidance. That’s why I break down each topic step-by-step and ensure you truly understand the “why” behind every concept. I also help students prepare for coding interviews, college exams, and build real-world projects. Whether you’re a beginner starting your coding journey or someone looking to improve problem-solving skills and crack top tech companies, I tailor my teaching approach based on your goals and current level. My aim is not just to teach you how to code, but to help you think like a problem solver and a strong Computer Science engineer. If you’re serious about improving and want clear, honest guidance, I’m here to help you grow consistently and confidently.

Meet Pranav

Coding tutor specialities

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Upskilling

Job readiness icon

Job readiness

Assignment help icon

Assignment help

Competitive Programming icon

Competitive Programming

Code Optimization icon

Code Optimization

Project help icon

Project help

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Paired coding

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AI modules

Summary

Podcast

Quiz

Learnings

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Zero Risk Guaranteed

15-days refund

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1-yr validity

24/7 support

Learner types for coding classes

Coding for intermediate icon

Coding for intermediate

Coding for beginners icon

Coding for beginners

Coding for kids icon

Coding for kids

Coding for advanced icon

Coding for advanced

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Hands-on learning

Students gain confidence applying coding skills to real projects.

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100% on-time college submissions

Students meet deadlines with tutor support.

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Flexible lesson scheduling

90% of students find it easy to schedule lessons.

Pranav - Coding tutor also teaches

C

C

C++

C++

Coding for kids

Coding for kids

CSS

CSS

HTML

HTML

Java

Java

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Coding concepts taught by Pranav

Student learned 10 days ago

The tutor and student reviewed the student's Python assignment code, clarifying concepts such as data generation, graph interpretation, and the logic behind specific variable calculations. They discussed the importance of foundational Python skills and data structures for problem-solving, and planned to continue with list operations in the next session.

Python Scripting: Code Review and Understanding

The Significance of Foundational Programming Skills

Data Structures: Lists and Dictionaries

Data Visualization Principles

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Student learned 11 days ago

The Tutor and Student reviewed data visualization techniques using Matplotlib for plotting sensor data (temperature, vibration, load). They practiced creating labeled graphs and focused on the implementation of highlighting anomalies by plotting red dots, preparing for further discussion on metrics and assignment completion.

Introduction to Libraries: `random`

Visualizing Anomalies

Handling Multiple Data Series

Customizing Plot Appearance

Matplotlib Plotting Basics

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Student learned 12 days ago

The Student and Tutor completed the Python coding for a sensor monitoring system, covering sensor data generation, anomaly detection, and CSV logging with real-time timestamps and automated data collection. They also implemented functions for statistical analysis of the logged data and received an introduction to Matplotlib for data visualization. The next session will focus on completing the visualization aspect of the assignment.

Real-time Data Logging to CSV

Automating Data Generation & Logging

Calculating Basic Data Statistics

Introduction to Data Visualization with Matplotlib

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Student learned 13 days ago

Student and Tutor covered Python file handling, including writing, reading, and appending to text files, as well as working with CSV files. They also learned about functions and applied these concepts to build functions for generating mock sensor data and detecting anomalies, directly addressing the requirements of the Student's assignment. The plan is to complete the assignment in the next class and then move on to data visualizations.

Introduction to File Handling & Data Persistence

Working with CSV Files in Python

Python Functions: Reusability and Structure

Simulating Sensor Data & Anomaly Detection

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Student learned 14 days ago

The Tutor and Student began reviewing a Python assignment to build a robotic arm monitoring system. They covered simulating sensor data using Python's `random` module, implementing anomaly detection with conditional logic, and discussed data logging into JSON/CSV files and the use of the `matplotlib` library for visualization. Future sessions will focus on file handling and data visualization theory.

Introduction to Data Visualization with Matplotlib

Python Lists for Data Collection

Structured Data Logging (JSON & CSV Concepts)

Anomaly Detection using Control Logic

Simulating Sensor Data with Python's `random` Module

Robotic Arm Monitoring System Overview

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Student learned 13 days ago

The Student and Tutor reviewed key concepts of distributed databases in preparation for an upcoming exam. They covered the definition, problems with centralized systems, advantages and disadvantages of distributed databases, and the distinction between distributed processing and distributed databases. The session also detailed the components of a distributed database system and different types of transparency, with the Tutor sharing notes for revision.

Distributed Databases: Core Concepts & Rationale

Distributed Processing vs. Distributed Databases

Components: Transaction Processor (TP) & Data Processor (DP)

Distributed Database Transparency

Types of Transparency: Location

Fragmentation

Replication

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Approach & tools used by coding tutor

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PyCharm

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Git & GitHub

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Visual Studio Code

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Google Colab

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Bitbucket

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