Data Science Series • Introduction to Data Science
For one on one session reach out at: [email protected] or +254707967928
BUCKET LIST IN THIS SERIES:
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Programming Languages:
• Python: The backbone of our course
• R: Another powerful language for statistical computing
Data Manipulation and Analysis Tools:
• Spreadsheets: For basic data handling and analysis
• SQL: To work with relational databases
• Power BI: For creating interactive data visualizations
Python Libraries:
• Pandas: For data manipulation and analysis
• NumPy: For numerical computing
• SciPy: For scientific computing
• Matplotlib and Seaborn: For data visualization
• Scikit-learn: For machine learning
Key Concepts and Techniques:
• Regression analysis
• Natural Language Processing (NLP)
• Data cleaning and preprocessing
• Exploratory Data Analysis (EDA)
• Statistical inference
• Machine Learning algorithms
• Big Data processing
Practical Application:
• 20 real-world projects to apply your skills
Join this channel to get access to perks:
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