Organizations today are overwhelmed with data; Data that, if treated properly, can render a tremendous competitive advantage in terms of reducing waste and increasing revenues. Data science is the science of generating valuable insights and predictions from data. Python is the most popular programming language for doing data science. This 5-day live certification course gives participants a solid foundation for doing data science in Python, so that they can earn an advantage and return to their organizations and apply data science to generate insights from business data.
Participants will be led through a series of lectures and hands-on exercises. Following each set, they will work through and practice writing Python code to perform data science tasks. Participants will come away from this course with data science coding experience, unique print-outs, and practical demonstrations and exercises that they can take to their organizations and apply for customized analyses. As part of this course, participants will complete an end-to-end data science project.
By the end of the course, participants will be able to:
- Clean, reshape, reformat, and describe data
- Generate data visualizations for desktop viewing and for interactive web-based display
- Spot and remove outliers
- Generate predictions using machine learning methods
- “Scrape” the internet to generate data sources
- Visualize and analyze spatial and network data
This course is designed for working professionals who want to use business data to make improved decisions through predictive analytics. This includes, but is not limited to, technical professionals such as database administrators, system administrators, business analysts, business intelligence specialists, GIS specialists, and web developers. Recommended pre-knowledge includes experience analyzing data in Excel, as well as a basic understanding of correlation, probability, and statistics. Participants should have prior experience working with data that is stored in traditional relational database systems. Some experience with an object-oriented programming language would be useful, but is not required.
- Data cleaning
- Data visualization
- Data analysis
- Predictive modeling
- Python programming