Data Science Course with Python by AnahuacX

Course Description

This Data Science course offers a comprehensive introduction to the field through Python programming. You will explore general concepts of data science such as statistical techniques, data mining, and machine learning, employing Python's rich library ecosystem supported by its vast community.

What Students Will Learn

• Understanding the significance of data science and its practical relevance.
• Learning the necessary tools for venturing into the world of Data Science via Python programming.
• Mastering the tools necessary to manipulate, analyze, and acquire data collections from the web.
• The fundamentals of proper data collection and preparation in data science studies.
• Gaining expertise in data visualization and the various approaches to visually represent data sets.
• Familiarizing with key database concepts and major database management systems.

Prerequisites

Basic programming knowledge is required to fully benefit from this course.

Course Content

• Introduction to Data Science and Python Programming Basics
• Data Collection and Preparation Techniques
• Data Visualization with Matplotlib
• Database Management and Introduction to SQL

Who This Course Is For

This course is designed for individuals looking to start their journey in the field of Data Science, particularly those with some programming background and interest in using Python for data analysis and visualization.

Real-World Application

Skills acquired in this course can be applied in various industries for data analysis tasks, predictive modeling, and strategic decision-making. Proficiency in Python and its libraries for data science empowers professionals to handle real-world data sets effectively, make informed decisions, and contribute to data-driven solutions in business, healthcare, finance, and more.

Course Syllabus

Week 1: Introduction - Setup essential software, learn Python basics including variable types, control structures, functions, and data structures.

Week 2: Data Collection and Preparation - Utilize Pandas for data management, learn web scraping, and explore data cleaning methods.

Week 3: Data Visualization - Create various charts and visualizations using Matplotlib to effectively communicate findings.

Week 4: Database Management - Introduction to databases and SQL for database handling.