The Data Science Complete Course by Neha Pandharpurkar is designed for beginners to advanced learners who want to build a strong foundation in Data Science, Python programming, statistics, machine learning, and SQL. This course covers all essential tools and techniques required for a career in Data Science and Analytics.

Through hands-on exercises, real-world datasets, and mini-projects, students will develop practical skills to analyze, visualize, and model data effectively.

What Students Will Learn

• Python Programming:

  • Basics to advanced Python

  • Variables, data types, loops, functions, and object-oriented programming

  • Libraries for data analysis: NumPy, Pandas

• Statistics for Data Science:

  • Descriptive statistics: mean, median, mode, variance, standard deviation

  • Probability concepts and distributions

  • Correlation, regression, and hypothesis testing

• Data Analysis & Visualization:

  • Data cleaning and preprocessing

  • Exploratory data analysis (EDA)

  • Visualizations with Matplotlib, Seaborn, and Tableau

• Machine Learning:

  • Supervised Learning: Linear Regression, Logistic Regression, Decision Trees, KNN

  • Unsupervised Learning: Clustering (K-Means), Dimensionality Reduction

  • Model evaluation and improvement

• SQL & Databases:

  • MS SQL and T-SQL basics

  • Data retrieval, queries, joins, and aggregation

  • Integrating SQL with Python for data analysis

• Practical Projects:

  • End-to-end Data Science mini-projects

  • Real datasets for predictive modeling, analytics, and visualization

  • Capstone project to consolidate learning

Teaching Method

This online course uses a hands-on, project-based approach:

• Live coding demonstrations and interactive Python exercises

• Real-world datasets for practice and analysis

• Mini-projects and a final capstone project

• Guidance for problem-solving, debugging, and best practices

Learners gain practical experience, technical confidence, and readiness for real-world data challenges.

Why This Tutor

Neha Pandharpurkar is an experienced Data Science and Python trainer. She emphasizes clarity, practical learning, and stepwise skill building, ensuring students understand both theory and its application in real datasets.

Benefits / Outcomes

By the end of this course, students will be able to:

• Write advanced Python programs for data processing

• Perform data cleaning, analysis, and visualization using Python and Tableau

• Apply machine learning algorithms for predictive modeling

• Write SQL queries to extract and manipulate data efficiently

• Handle real-world datasets and implement end-to-end Data Science projects

• Prepare for Data Science roles, internships, or academic projects

This course is suitable for students, professionals, and career switchers aiming for a career in Data Science, Analytics, or AI.