AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
Overview
Master the critical data transformation skills that turn messy, real-world data into analysis-ready formats. This course tackles two of the most common yet challenging data quality issues facing analysts today: extracting structured data from complex JSON and fixing timezone inconsistencies that corrupt datasets.
This Short Course was created to help data analysis professionals accomplish reliable data preprocessing that enables accurate downstream analytics.
By completing this course, you'll be able to confidently handle the data wrangling challenges that cause delays and errors in production analytics pipelines. You'll transform from struggling with nested data structures to efficiently processing complex JSON with pandas, and from manually detecting time discrepancies to systematically correcting timezone offsets that fragment user sessions.
By the end of this course, you will be able to:
Apply scripting techniques to flatten nested JSON data into relational columns.
Analyze time-based data to correct inconsistencies arising from timezone offsets.
This course is unique because it focuses on real production data quality issues using hands-on Python transformations that mirror actual workplace scenarios, not theoretical exercises.
To be successful in this project, you should have a background in Python programming, basic pandas operations, and familiarity with data analysis workflows.
Advantages and disadvantages
Advantages
- Structured courses with graded quizzes, assignments and deadlines you can reset.
- A shareable certificate from the university or company when you pay.
- Financial aid is often approved for students in India (apply 15 days before you need it).
- Self-paced: start any time.
Disadvantages
- Paid after a 7-day free trial (Coursera Plus or per course).
- Some courses can be audited for free, but graded work and certificates need payment.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
- Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
- Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
Coursera is in Tier 4: commercial training companies and platform-made courses of our institution ranking (56/100). Made by the platform, often short guided projects.
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