Podcast
Questions and Answers
Which of the following topics are included in the Mathematics section?
Which of the following topics are included in the Mathematics section?
What is one of the courses listed under Statistics?
What is one of the courses listed under Statistics?
Coursera: Introduction to Statistics
What is a prerequisite of Econometrics mentioned?
What is a prerequisite of Econometrics mentioned?
Fundamentals of econometrics
Which model is associated with Time Series analysis?
Which model is associated with Time Series analysis?
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The document includes references to papers and articles about statistical tests and experiment design.
The document includes references to papers and articles about statistical tests and experiment design.
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Which platforms offer courses related to this roadmap?
Which platforms offer courses related to this roadmap?
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Name one article related to hypothesis testing from the document.
Name one article related to hypothesis testing from the document.
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Study Notes
AI and Data Science Roadmap by Careem
- Created by the AI and DS team at Careem, affiliated with Uber.
- Acknowledgements to creators @mohamadtweets and @BulatShkanov.
- Available resources and roadmaps can be found at roadmap.sh.
Mathematics Foundations
- Essential areas include linear algebra, calculus, and mathematical analysis for AI and data science.
- Courses available on Coursera cover foundational topics such as:
- Introduction to Statistics
- Algebra and Differential Calculus
- Hypothesis Testing
- Probability and Statistics.
Econometrics
- Offers insights into regression analysis, time series, and statistical methods.
- Important resources include:
- "Intro to Econometrics" book.
- Coursera's Econometrics course for practical understanding.
- Key concepts include hypothesis testing and A/B testing, with articles that act as guides.
Time Series Analysis
- Tutorials available on Kaggle to learn time series fundamentals.
- ARIMA model techniques covered to predict and analyze time series data.
- Resources supporting this field include:
- Open-source projects focused on forecasting tasks.
- Papers on statistical tests' sensitivity, including CUPED (Control for Unit-specific Effects for Demand).
Coding Skills
- Proficiency in Python is emphasized, with courses tailored for all levels:
- Google's Python Class for beginners.
- Kaggle courses focused on Python programming.
- Exploratory Data Analysis (EDA) skills include:
- Understanding data through analysis, visualization, and Python libraries like Pandas.
- Specialized courses in EDA for machine learning applications.
Key Concepts in Probability and Statistics
- Central Limit Theorem (CLT) as a cornerstone of statistical inference.
- Practical implications of experiment design and test sensitivity explored via various articles and papers.
Additional Resources
- Various educational platforms offer courses that reinforce learning paths.
- Papers provide deep dives into specialized metrics and methods like the Delta Method in Analytics and Ratio Metrics.
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Description
Explore the comprehensive AI and Data Science roadmap created by the Careem team. This roadmap outlines essential resources and various pathways to advance your expertise in the fields of AI and data science.
