AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
Overview
Apply various data analysis and visualization skills and techniques you have learned by taking on the role of a data scientist working with real-world data sets.
What you'll learn
- Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
- Do exploratory data analysis using descriptive statistics, data grouping, data analysis and correlation statistics.
Skills you'll practise
Advantages and disadvantages
Advantages
- University courses you can audit for free, with lectures, readings and practice quizzes.
- A verified certificate from the university if you pay for it.
- From IBM, a well-regarded name.
- Self-paced: start any time.
- Hands-on: you build or practise, not just watch.
Disadvantages
- Graded assignments and the certificate need the paid track.
- Audit access can expire a few weeks after the course ends.
- Learning is free, but the certificate costs money.
- Some parts (graded work, certificate) are paid.
Some points apply to every course of this kind; see how we rank.
Free to audit
- Free: Choose "Audit this course" when you enrol: lectures, readings and practice are free.
- Paid: Graded assignments and the verified certificate (Certificate $99). Audit access may end after the course closes.
Taught by
- Yan LuoPh.D., Data Scientist and Developer
- Jeff GrossmanData Science and Engineering SME
IBM is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (84/100).
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