Enterprise Data Science in Practice
Course provided by IBM
About this course
- Understand the composition and working of a Data science team
- Find structure in data and make predictions
- Internalise the data science methodology
- Construct usable data sets by identifying and collecting the data required
- Hands-on experience with IBM Watson Studio and Python libraries
- Visualise statistical analysis, identify patterns and effectively communicate findings
How does it work?
- This course is divided into three practice levels to progress through at your own pace.
- Each level covers more advanced topics and builds up on top of the concepts, practice and skills addressed on the previous practice levels.
Who should take this course
- If youve already got some experience and knowledge in data science, this course will allow you to build on those foundations to solve real challenges within the enterprise.
- If you are interested in the impact of data science on the enterprise and how to leverage AI-powered technologies, this course could be perfect for you.
- EITHERComplete the Getting Started with Enterprise Data Science course from the Data Science Series.
- OR You will need prior knowledge on the following subjects before joining this course:
- The relevance of data science projects in supporting the digital transformation of business across multiple industries.
- Data science cross-disciplinary skillset found at the intersection of statistics, computer programming and domain expertise.
- Roles of a Data science team: Data scientist, Data engineer, Data analyst and AI developer.
- Data science collaboration platforms in the cloud, including IBM Watson Studio and Data Refinery.
- Data ingestion and manipulation using a CSV dataset.