Learn in-demand skills like statistical analysis, Python, regression models, and machine learning in less than 6 months.
What you'll learn
- Explore the roles of data professionals within an organization
- Create data visualizations and apply statistical methods to investigate data
- Build regression and machine learning models to analyze and interpret data
- Communicate insights from data analysis to stakeholders
- Data Science
- Regression Models
- Predictive Modelling
- Exploratory Data Analysis (EDA)
- Statistical Analysis
- Machine Learning
- Python Programming
- Data Analysis
- Jupyter Notebook
- Tableau Software
- Data Visualization (DataViz)
- Kaggle
Course 1 • 22 hours
- 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
Course 2 • 28 hours
- 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
Course 3 • 26 hours
- 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
Course 4 • 30 hours •
- 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
Course 5 • 24 hours •
- Investigate relationships in datasets
- Identify regression model assumptions
- Perform linear and logistic regression using Python
- Practice model evaluation and interpretation
Course 6 • 29 hours •
- 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
Course 7 • 8 hours •
- Examine data to identify patterns and trends
- Build models using machine learning techniques
- Create data visualizations
- Explore career resources