Introduction to Data Science & Project Lifecycle
Project Overview - Description: This day introduces the core concepts of data science and the process of managing a data science project. It will cover what data science is, the types of problems it solves, the roles within a data science team, and a high-level overview of the data science project lifecycle. It also introduces the concept of project planning and defining project goals. - Resources/Activities: - Expected Outcome: Understanding of what data science is, its value, the typical roles involved, the project lifecycle, and the ability to formulate a basic project goal.
Learning Objectives
- Understand the fundamentals
- Apply practical knowledge
- Complete hands-on exercises
Understanding Data & Data Sources
Project Scope - Description: Learn about different types of data (structured, unstructured, etc.) and where data is sourced from. Learn how to gather information and establish the scope of a data science project. Learn to identify and understand the types of data that would be used in a project. - Resources/Activities: - Expected Outcome: Understanding of various data types, the importance of data sources, and the ability to identify potential data sources and understand data scope for a project.
Learning Objectives
- Understand the fundamentals
- Apply practical knowledge
- Complete hands-on exercises
Data Science Tools & Environments
Tool Familiarization - Description: Explore essential tools and environments commonly used in data science, with a focus on ease of use for beginners. This includes choosing an IDE (Integrated Development Environment) like Google Colab or Jupyter Notebook and becoming familiar with its interface. - Resources/Activities: - Expected Outcome: Familiarity with the basic operations of a data science development environment and the ability to create simple code and text cells.
Learning Objectives
- Understand the fundamentals
- Apply practical knowledge
- Complete hands-on exercises
Introduction to Data Exploration and Cleaning
Data Acquisition - Description: Begin exploring a dataset. Learn about the fundamentals of data exploration. Introduce basic data cleaning techniques. Focus on loading data, viewing basic statistics, and handling missing values. - Resources/Activities: - Expected Outcome: Ability to load a dataset, perform basic exploratory analysis, and identify missing values.
Learning Objectives
- Understand the fundamentals
- Apply practical knowledge
- Complete hands-on exercises
Version Control and Collaboration – Preparing the Project for Teamwork
- Description: Understand the basics of version control (using Git and GitHub). Learn how to create a repository and commit changes to your project. Introduce basic principles of collaboration. - Resources/Activities: - Expected Outcome: Understanding the value of version control, familiarity with Git and GitHub, and ability to create a project repository and commit your initial code.
Learning Objectives
- Understand the fundamentals
- Apply practical knowledge
- Complete hands-on exercises
Ethics and Data Privacy
Project Planning Refinement - Description: Introduce data ethics and the importance of responsible data science. Learn about data privacy considerations. Focus on identifying and mitigating ethical concerns related to your chosen project. - Resources/Activities: - Expected Outcome: Understanding of ethical considerations in data science and the ability to apply ethical principles to your project plan.
Learning Objectives
- Understand the fundamentals
- Apply practical knowledge
- Complete hands-on exercises
Project Documentation and Communication
Wrapping Up and Presentation - Description: Learn the importance of project documentation and communication. Start building the documentation for your project. Practice summarizing your project and communicating its goals, methodology, and results in a clear and concise way. - Resources/Activities: - Expected Outcome: Understanding the importance of good documentation and communication, and the ability to document your project and present it in a clear and concise manner.
Learning Objectives
- Understand the fundamentals
- Apply practical knowledge
- Complete hands-on exercises
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