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In this course, you will :
- Explore the functions of data specialists within a company.
- Create data visualisations and examine data using statistical methods.
- To analyse and interpret data, create regression and machine learning models.
- Stakeholders should be informed of the findings of data analysis.
Syllabus :
1. Foundations of Data Science
- Understand common careers and industries that use advanced data analytics
- Investigate the impact data analysis can have on decision-making
- Explain how data professionals preserve data privacy and ethics
- Develop a project plan considering roles and responsibilities of team members
2. Get Started with Python
- Explain how Python is used by data professionals
- Explore basic Python building blocks, including syntax and semantics
- Understand loops, control statements, and string manipulation
- Use data structures to store and organize data
3. Go Beyond the Numbers: Translate Data into Insights
- Apply the exploratory data analysis (EDA) process
- Explore the benefits of structuring and cleaning data
- Investigate raw data using Python
- Create data visualizations using Tableau
4. The Power of Statistics
- Explore and summarize a dataset
- Use probability distributions to model data
- Conduct a hypothesis test to identify insights about data
- Perform statistical analyses using Python
5. Regression Analysis: Simplify Complex Data Relationships
- Investigate relationships in datasets
- Identify regression model assumptions
- Perform linear and logistic regression using Python
- Practice model evaluation and interpretation
6. The Nuts and Bolts of Machine Learning
- Identify characteristics of the different types of machine learning
- Prepare data for machine learning models
- Build and evaluate supervised and unsupervised learning models using Python
- Demonstrate proper model and metric selection for a machine learning algorithm
7. Google Advanced Data Analytics Capstone
- Examine data to identify patterns and trends
- Build models using machine learning techniques
- Create data visualizations
- Explore career resources
