DAT 110 - Data Analytics and Visualization for Business
Course Description
Equip yourself with the fundamental knowledge of applied data science. Explore the analytic process, analytic problem-framing, statistics foundation, data preparation, and visualization to optimize organizational performance. Students will gain hands-on experience wrangling data of different types and shapes. Learn how to summarize and derive insight from data through visualization and dashboarding.
The course is designed with comprehensive lab activities and a hands-on mini-project.
This course is delivered in collaboration with WeCloudData.
Course Details
Learning Outcomes
By the completion of this course, successful students will be able to:
- Apply data transformation on structured data using Python data analysis library Pandas
- Apply basic statistical analysis and data visualization on structured data using Python’s scientific computing libraries such as Numpy and Scipy
- Evaluate use cases of data analytics such as cohort analysis, segmentation, visual story telling, etc. in the financial, telecommunications, and SaaS industries
- Explain the general data analytics processes including the tools and steps required.
- Learn how the processes can be adapted to different analytics use cases
- Implement data visualization dashboards with tools such as PowerBI or Python
- Develop key business performance, opportunities and challenges that help business stakeholders
Topics
- Python Programming Refresher
- Data Science Workflow
- Data Wrangling Basics
- Statistics Essentials for Data Visualization
- Data Exploration and Visualization with Python
- Visual Storytelling with PowerBI Dashboard
Who is this course for?
This course is designed for:
- Business associates, project managers
- Professionals from every level or industry who work with analytics or data
- BI/Data analysts who want to go beyond Excel and improve their data handling and visualization skills
- Recent graduates and academics in Computer Science
- Individuals who are aspired to pursue career opportunities like Data Analyst, Data Science Analyst, Data Scientist
Notes
Software Requirement
To complete the lab activities and mini-project, you will require:
- Anaconda Python Distribution or Google Colab
Prerequisites
There are no mandatory prerequisites for this course. However you are required to perform a self-assessment to ensure you meet the requirements to enrol.
Self-assessment for enrolment
- A minimum of 6 months of experience in python programming.
Recommended pre-requisites:
Applies Towards the Following Program(s)
- Machine Learning and Visualization : Required