Lesson
1
🔑 Recap of key concepts
Data Science
A field that combines domain expertise, programming skills, math, and statistics to extract meaningful insights from data.
Data Scientist
Responsible for collecting, analyzing, and interpreting large datasets to provide actionable insights.
Data Analysis
Data analysis is the practice of working with data to find useful information and understand past patterns to make better decisions.
Machine Learning
An AI technique that lets computers learn from data to make predictions and recognize patterns without explicit programming.
Artificial Intelligence
The technology that allows machines to understand/interpret, learn, and make “intelligent” decisions. It includes Machine Learning among many other fields and is used in the field of Data Science for its operations.
❓ Questions
What is Data Preparation?
The process of preparing the data by handling missing or messy information before using it.
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What is the difference between Data Science and Data Analytics?
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AI technique that allows computers to learn patterns and make predictions from data.
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🪜 Project Steps
  • Log in or sign up on LinkedIn.
  • Open the “Write an article” editor from the Home tab.
  • Write your title and article content.
  • Format with headings, subheadings, short paragraphs, and bullet points.  
  • Review for clarity, grammar, and spelling.
  • Publish the article.  
  • Share the link with your network and groups.
⚡ Quick Tips
  • Make your title catchy to attract readers.
  • Keep paragraphs short and readable.
  • Organize ideas with headings and bullet points.
  • Use images, videos, or links to illustrate points and support your ideas.  
  • Keep a professional and clear tone. 
  • Proofread before publishing to fix mistakes. 
  • Add tags and a featured image to reach more people. 
  • Preview your article to check formatting.
📝 Task
  • Write an article on LinkedIn about the importance of data science in businesses.
    • Explain how data-driven insights help companies make better decisions.
    • Explore different aspects of data science and how it can give businesses a competitive edge.
    • 📖 Glossary
  • Data Science
    The field that uses domain expertise, programming, and math and statistics to extract knowledge.
    Machine Learning
    An AI technique where algorithms learn from data.
    Data Scientist
    A storyteller presenting data insights to decision-makers in a way that is understandable and applicable to problem-solving.
    Data Analysis
    The practice of working with data to glean useful information that can be used to make informed decisions.
    🔗 Resources
    ⬆️ Upload Project Steps
    • Don't forget to upload your project.
    🔮 Next Session Preview
    • Learn what Google Sheets is and why it’s useful for data analysis.
    • Differences between Excel and Google Sheets. 
    • Explore rows, columns, cells, and the Ribbon interface.
    • Using Google Sheets for data analysis and learn simple formulas.   
    • Creating charts and graphs.