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HomeCoursesAi & Machine LearningEssential Math for AI Programming & Data Structures

Essential Math for AI Programming & Data Structures

By edX with Columbia University

AI & Machine Learning

7.2
•1 verified reviewTrustScore
Our ratings use a 10-star system for more precise quality assessment
Online Course
8 hours
Intermediate
Certificate Included
Visit Provider
Write a ReviewWrite a Story
TrustCourse Rating
Verified
B-
TRUST·SCORE
7.2
OUT OF 10
1 verified review
Good
Rating Distribution% of reviews
9-10
0%
8-9
0%
7-8
100%
6-7
0%
0-6
0%

DETAILED RATINGS

Content Quality
7.0
Instructor Delivery
7.0
Platform Experience
7.0
Value For Money
8.0
Learning Outcome
7.0
All reviews are verified by TrustCourse

Course Syllabus

1

Course 1 • Essential Math for AI - Discrete Mathematics

2

Course 1 • Essential Math for AI - Calculus Fundamentals

3

Course 1 • Essential Math for AI - Linear Algebra Concepts

4

Course 1 • Essential Math for AI - Probability Theory

5

Course 2 • Programming & Data Structures - Python Fundamentals

6

Course 2 • Programming & Data Structures - Data Structures Review

7

Course 2 • Programming & Data Structures - AI Applications

TrustCourse AI AnalysisAI Generated
Based on public data analysis
•
Updated May 28, 2025
7.2/10
Good

Course Goal

Review and refresh key mathematical concepts including discrete math, calculus, linear algebra, probability theory, and programming fundamentals to prepare for advanced AI coursework.

One-Minute Verdict

Solid math refresher from prestigious Columbia University, but limited recent student feedback makes it hard to assess current effectiveness and content freshness.

PROS

  • Columbia University credential and academic rigor
  • Two-part structure covering both math and programming essentials
  • Self-paced format accommodates working professionals

CONS

  • Limited recent student feedback and reviews available
  • Positioned as refresher, may not suit complete beginners
  • Requires existing programming and math background

DETAILED AI RATINGS

Content Quality
7.0/10

Covers essential AI math topics from Columbia University. Positioned as refresher rather than comprehensive treatment, may lack depth for complete beginners.

Instructor Delivery
7.0/10

Professor from Columbia CS department with NLP expertise. Limited specific feedback available but institutional reputation suggests quality instruction.

Platform Experience
7.0/10

edX platform generally reliable with university-backed content. Users report interface could be more engaging and certificates are expensive.

Value For Money
8.0/10

At $135 discounted from $150 for Columbia certificate, reasonable pricing for prestigious university credential in AI fundamentals.

Learning Outcome
7.0/10

Should adequately prepare learners for advanced AI courses. Two-part structure covers both math and programming prerequisites effectively.

DECISION GUIDE

Take This Course If

You have programming experience and need to refresh math fundamentals before advanced AI study

Ideal bridge course for those with technical background looking to formalize their AI mathematics knowledge with prestigious credential.

Skip This Course If

You're a complete beginner to programming or mathematics

Prerequisites include Python experience and advanced math performance; not designed as introductory course for absolute beginners.

SOURCES & REFERENCES

  • https://www.edx.org/certificates/professional-certificate/columbiax-essential-math-for-ai-programming-data-structures
  • https://www.reddit.com/r/learnprogramming/comments/bol4fb/what_mathematics_do_i_need_for_aimachine_learning/
  • https://www.capterra.com/p/230243/edX/reviews/
  • https://www.classcentral.com/course/columbiax-essential-math-for-ai-programming-data--436153
  • https://www.edx.org/learn/computer-science/columbia-university-essential-math-for-ai

About this AI Summary

This summary is generated by AI based on public internet data, including social networks and available articles.

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