Master Data Science with SQL and Python
- 网络技术
- 2025-08-31
- 10
Published 11/2024
Created by Desmond Otieno Onam
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 28 Lectures ( 33h 13m ) | Size: 12.4 GB
Data Science Course with Python and MySQL
What you’ll learn
Introduce Python basics and the its use in Data Science
Introduce MySQL and integration with python
Data Analysis and Visualization
Machine Learning from Basics to advanced
Requirements
There are no prior requirement’s. This is a complete beginners course.
Description
This course comprehensively introduces data science using Python and MySQL, combining essential data manipulation, analysis, and database management skills. You’ll learn Python’s powerful data science libraries, including Pandas, NumPy, and Matplotlib, to clean, analyze, and visualize data. Additionally, you’ll gain hands-on experience with MySQL, mastering SQL queries, database creation, and data management techniques to store and retrieve data efficiently.Through real-world projects, you will explore the entire data science pipeline—data collection, storage, analysis, and visualization—while understanding how Python and MySQL integrate to solve practical problems. By the end of this course, you’ll be able to manipulate and analyze datasets, create insightful visualizations, and work confidently with databases, equipping you with the skills to handle diverse data science challenges in any professional setting. Suitable for beginners and intermediates.You’ll also delve into key statistical concepts and machine learning basics, applying predictive models to extract insights from data. The course emphasizes practical applications, guiding you through structured exercises and real-world datasets to reinforce your understanding. With Python, you’ll automate data workflows and create interactive dashboards, while MySQL enables you to efficiently manage and query complex datasets. By the end, you’ll have a robust toolkit for tackling data science tasks, from initial data exploration to delivering data-driven insights and actionable recommendations across various industries.
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