

Udacity's AI Artificial Intelligence Nanodegree offers a comprehensive exploration of AI foundations. Delivered online, this self-paced program delves into search algorithms, symbolic logic, and planning systems through project-based learning. It's designed to equip learners with practical AI skills applicable across various industries.
Ideal for aspiring AI professionals and enthusiasts
Open to both technical and non-technical backgrounds
No prerequisites required for enrollment
Self-paced online learning with flexible schedules
Project-based exercises focused on AI techniques
Access to a supportive community for collaboration
Earn a Nanodegree certificate upon completion
Develop foundational AI skills and techniques
Enhance career prospects in AI and related fields
No certifications are covered by this course.
Student 2022
I know well that artificial intelligence is future. That's why I choose this course. One of my friend suggested Udacity to have my learning platform. My instructors are great. They teach me in very lucid way.
Student 2020
Enjoyed the Class. Well organized content and easy to follow.
Student 2020
Only just finished the first week of the AI Nanodegree.High quality video content, well presented. Comparable to Andrew NG's Deep Learning Specialization or the MITx Pro Quantum Computing Fundamentals course.Technical unit tests using an IDE feel better than editing half written functions in Jupyter notebook (with an autograder), or random example code.Quizzes have explanations videos, which is improvement over the Coursera quiz model.I like how you include textbook readings, extracurricular submodules and content links to other courses.Overall, this feels very much like an online university course. Impressed!
Graduate 2018
Great for learning a new skill. The instructors are available using Slack and are quick to communicate back. The mentors are a great help when you get stuck.
Student 2019
Instructors explained course material extremely well and clearly.
Assitant gave exellent feedbacks for the submitted projects
Student 2019
The program is awesome, good enough for beginners to make career in AI ML.
Graduate 2018
Good material, but projects were simple and the review for each project was terrible, the AI reviewers are very bad, nothing compared to other reviewers like Web, Android, iOS, React...
Graduate 2017
If you're an experienced coder and are curious about taking Udacity's AI nanodegree, there were five things that helped me make a decision.
I wish future me would have sent me this info back when I was trying to decide. I could have saved lots of time and fear of wasting my money.
Well, future me is here now. I wrote this review in hopes it will help you make your decision to go forward with the Udacity AI nanodegree or not.
[ to see the entire post goto [http://www.thedevpreneur.com/2017/11/26/udacity-ai-nano-degree-review-coders/]
1) Self learning AI is not working for you
How the Udacity AI nanodegree is better than self learning:
Provided a clear definition of "artificial Intelligence" beyond the trivial wikipedia version
A structured list or map of all the areas of AI and how they relate.
Created clarity on how to clarify problems to identify how to solve them with our without AI.
Because I had to drop big $$$, I got a sense of urgency and co
mmitment. This drove me to carve out time in my week and get it done.
Focused in on the key areas of AI. There is way too much information out there, I got guidance on whats hot and making the biggest impacts in the field of AI.
As trivial as these points seemed, the nanodegree gave me a new perspective. It provided me understanding beyond what I could price together on my own. It also gave me focus and forced me to commit to learning in a finite time frame.
2) You hate reading white papers
Here are some ways Udacity structured the information:
Simple animated illustrations for complex topics. This was one of the best parts of the content.
Ease in beginners to reading white papers and only require some reading to complete some projects.
Introductory lessons on math notations and core CS concepts needed to understand AI white papers.
The instructor team acknowledged that white papers are currently the best source for latest on AI advancements. The cool thing is that material only referenced white papers as additional reading in most lessons.
Bottom line the Udacity Material is way more beginner friendly than anything I have come across for free on the web .
3) You keep looking for the AI hello world example
How Udacity was not too academic:
Although the general structure was still academically oriented and bottom up, they broke theory up into small consumable pieces.
Lessons were supplemented with practical examples to reinforce what was taught.
Many of the examples provided, were based on real problems being solved in industry.
The AI nanodegree still feels academic in nature but had enough practical examples to keep me interested.
4) You have a hard time justifying the price
How Udacity was more than an online course:
The team at Udacity will assign a personal mentor to give you 1 on 1 answers and guidance.
A career prep supplement with resume writing and networking tips and best practices.
Very active Slack community covering industry news, events, project discussion and contests.
Multiple required projects with code reviews and automated tests with scoring rubrics.
Life time access to all content with future updates.
Even with all these add-ons, the cost felt a little on the higher end of what I'm comfortable with. Add-ons like the career advice is more targeted to junior candidates. On the other hand, the 1 on 1 mentor was very valuable and something you don't get with typical online courses.
5) You don't feel you meet the prerequisites
The prerequisites your really need before you take the Udacity AI nanodegree:
Python basics with focus on looping, recursion and data structures
Using jupyter notebooks with python
Condition and non-conditional probability basics.
Some calculus with focus on derivatives if you really want to get into the theory.
Very basic linear algebra with focus on matrics multiplication.
The area that slowed me down the most was not the math. The Ai nanodegree covered most of the math in refreshers and intros. I did struggle with figuring out efficient way to manipulate data using python and data libraries like numpy.
Don't get intimidated by the math prerequisites. If you're a good coder you shouldn't have too much difficulty getting through it.
I still would highly recommend doing as much pre learning in all the math areas mentioned. If you want to get the most for your $$$, you need to understand the theory and that requires understanding the math.
So was it worth it?
I had a positive experience with the AI nano-degree and would recommend it to any developer willing to drop the $$$. Go for it if you're looking for the fastest way to learn a whole boat load of AI in a relatively short time. Just like any paid education, you get out of it what you put in. So make sure you prep well and slice out enough time in your week to maximize your learning.
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