Data Science Course by Navneet Kumar

Course Overview

This comprehensive Data Science course covers essential topics such as Python programming, statistics, data analysis, machine learning, and deep learning. Designed for beginners and those looking to enhance their skills, this course is perfect for students, professionals, and anyone interested in pursuing a career in data science. By enrolling, you will gain practical skills that are directly applicable in the industry, making you a valuable asset in today's data-driven world.

What Students Will Learn

1. Python for Data Science

Python Fundamentals (Variables, Data Types, Loops, Functions)

Object-Oriented Programming (OOP)

NumPy for Numerical Computing

Pandas for Data Manipulation

Data Cleaning & Preprocessing

Working with CSV, Excel & APIs

Mini Project: Sales Data Analysis

2. Statistics & Mathematics

Descriptive Statistics

Probability Theory

Data Distributions (Normal, Binomial)

Hypothesis Testing

Correlation & Covariance

Linear Algebra Basics for ML

3. Data Analysis & Visualization

Exploratory Data Analysis (EDA)

Feature Engineering

Handling Missing Values & Outliers

Data Visualization using Matplotlib & Seaborn

Business Dashboard Overview (Power BI / Tableau)

Mini Project: Business Insights Dashboard

4. SQL for Data Analysis

Database Concepts

SELECT, WHERE, GROUP BY, HAVING

JOINS & Subqueries

Window Functions

Real-world Query Practice

Mini Project: Customer Insights Analysis

5. Machine Learning

Supervised Learning

Linear Regression

Logistic Regression

Decision Trees

Random Forest

K-Nearest Neighbors (KNN)

Model Evaluation Metrics

Unsupervised Learning

K-Means Clustering

Hierarchical Clustering

Principal Component Analysis (PCA)

Advanced ML Concepts

Feature Selection

Cross Validation

Hyperparameter Tuning

Pipeline Creation

Major Project: End-to-End ML Model

6. Deep Learning Basics

Introduction to Neural Networks

Artificial Neural Networks (ANN)

TensorFlow / Keras Basics

Image or Text Classification Mini Project

Teaching Method & Learning Approach

This course will be delivered in an online format, allowing for flexible learning. Navneet Kumar employs a concept-based and practice-oriented teaching style, ensuring that students not only understand the theory but also apply it practically. Interactive sessions will include hands-on projects, quizzes, and discussions to enhance student engagement and comprehension.

Why Learn From This Tutor

Navneet Kumar is dedicated to providing clear explanations and structured guidance throughout the course. His approach focuses on student support, offering assistance and feedback to ensure that each learner can progress confidently and effectively.

Location Context

While the course is offered online, students from Roorkee and neighboring areas will find it convenient to connect with a local tutor who understands regional industry needs.

Benefits & Learning Outcomes

By the end of this course, you will:

• Achieve concept clarity in data science fundamentals.

• Build confidence to tackle real-world data challenges.

• Improve your skills and readiness for exams or job opportunities in data science.