Hands-On Data Science Projects

Hands-On Data Science Projects

What you'll learn

Gain hands-on experience in data analysis and modeling using Python within Jupyter Notebooks.

Learn to manage and query databases using MySQL and its graphical interface, MySQL Workbench.

Develop interactive web applications for data visualization and machine learning model deployment.

Create dynamic and interactive dashboards to visualize complex datasets.

Requirements

Basic Understanding of Programming: Familiarity with any programming language, preferably Python.

Fundamental Knowledge of Databases: Basic understanding of database concepts and SQL.

Proficiency in Excel: Basic skills in using Excel for data manipulation and analysis.

Description

Welcome to the "Hands-on Data Science Projects" course! This comprehensive program is designed to equip you with practical skills and experience in data science through a series of real-world projects. Throughout this course, you will work with a variety of powerful tools and technologies, including Jupyter Notebook, Streamlit, MySQL Workbench, Power BI, and Excel. These tools will help you analyze and visualize data, build predictive models, and create interactive dashboards, giving you a robust and practical understanding of the data science workflow.You will start with an introduction to data analysis techniques and progress through various projects, each designed to provide hands-on experience with different aspects of data science.Tailored for students, aspiring data scientists, and professionals looking to enhance their data science skills, this course provides practical experience in solving real-world problems using industry-standard tools. You will learn to collect, clean, and analyze data, build and evaluate predictive models, and create interactive visualizations and dashboards. By the end of this course, you will be well-prepared to apply your data science skills in professional settings, equipped with a comprehensive portfolio of projects demonstrating your expertise. Embark on your journey with us and unlock boundless opportunities in data science and technology.

Overview

Section 1: Glass Type Prediction using Streamlit

Lecture 1 Project Description

Lecture 2 Glass Type Prediction using Streamlit

Lecture 3 Project File

Lecture 4 Dataset

Section 2: Car price prediction using streamlit

Lecture 5 Project Description

Lecture 6 Car price prediction using streamlit

Lecture 7 Project File

Lecture 8 Dataset

Section 3: Retail DB Analysis

Lecture 9 Project Description

Lecture 10 Retail DB Analysis

Lecture 11 Project File

Lecture 12 Datasest

Section 4: Vehicle Sales Analysis

Lecture 13 Project Description

Lecture 14 Vehicle Sales Analysis

Lecture 15 Project File

Lecture 16 Dataset

Section 5: Social Media Analysis

Lecture 17 Project Description

Lecture 0 Social Media Analysis

Lecture 18 Project File

Lecture 19 Dataset

Section 6: Music Streaming Application Analysis

Lecture 20 Project Description

Lecture 21 Music Streaming Application Analysis

Lecture 22 Project File

Section 7: Movies DB Analysis

Lecture 23 Project Description

Lecture 24 Movies DB Analysis

Lecture 25 Project File

Lecture 26 Dataset

Section 8: Avocado Sales Analysis Dashboard

Lecture 27 Project Description

Lecture 28 Avocado Sales Analysis Dashboard

Lecture 29 Project File

Lecture 30 Dataset

Section 9: HR Analytics Dashboard

Lecture 31 Project Description

Lecture 32 HR Analytics Dashboard

Lecture 33 Project File

Lecture 34 Dataset

Section 10: Data Professional Survey

Lecture 35 Project Description

Lecture 36 Data Professional Survey

Lecture 37 Project File

Lecture 38 Dataset

Section 11: Bike Store Analysis

Lecture 39 Project Description

Lecture 40 Bike Store Analysis

Lecture 41 Project File

Lecture 42 Dataset

Section 12: Space Mission Dashboard

Lecture 43 Project Description

Lecture 44 Space Mission Dashboard

Lecture 45 Project File

Lecture 46 Dataset

Section 13: Cinemalytics

Lecture 47 Project Description

Lecture 48 Cinemalytics

Lecture 49 Project File

Lecture 50 Dataset

Section 14: Monthly Sales Analysis

Lecture 51 Project Description

Lecture 52 Monthly Sales Analysis

Lecture 53 Project File

Lecture 54 Dataset

Section 15: Coffee Shop Sales Analysis

Lecture 55 Project Description

Lecture 56 Coffee Shop Sales Analysis

Lecture 57 Project File

Lecture 0 Dataset

Section 16: Python Analysis on AirBnB

Lecture 58 Project Description

Lecture 59 Python Analysis on AirBnB

Lecture 60 Project File

Lecture 61 Dataset

Section 17: Quality Analysis Dashboard

Lecture 62 Project Description

Lecture 63 Quality Analysis Dashboard

Lecture 64 Project File

Lecture 65 Dataset

Section 18: Film Database Analysis and Categorization

Lecture 66 Project Description

Lecture 67 Film Database Analysis and Categorization

Lecture 68 Project File

Lecture 69 Dataset

Aspiring Data Scientists,Data Analysts,Software Developers,Business Analysts,Students,Career Changers,Anyone Interested in Data Science Projects.