Free MIT.edu OpenWare Courses (OWC)

MIT.edu OCW

Designed for 6–7 months of structured, portfolio-driven study (10–12 hrs/week)

OCW study sequence for AI/ML and robotics foundations

Order	Course	Theme	Duration (weeks)	Application tie-in
0	6.S191 – Introduction to Deep Learning	Modern deep-learning foundations (CNNs, RNNs, Transformers)	4	TensorFlow/PyTorch hands-on intro; vision, NLP, biology
1	6.042J – Mathematics for Computer Science	Discrete math and graphs	3–4	SLAM topologies, graph optimization
2	6.041SC – Probabilistic Systems Analysis and Applied Probability	Probability and systems	4–5	Sensor fusion, Bayesian estimation, uncertainty modeling
3	6.036 – Introduction to Machine Learning	Core machine learning	4–6	Classification, regression, regularization
4	6.801 – Machine Vision	Vision and perception	4–5	Mapping, feature detection, optical flow, 3D reconstruction
5	6.4210 – Robotic Manipulation	Robotics and control	5–6	Motion planning, control loops, state estimation
6	9.01 – Introduction to Neuroscience	Biological neural systems	3–4	Sensory pathways, motor control, neural coding
7	9.13 – The Human Brain	Cognitive neuroscience	3	Perception, learning, memory architecture
8	9.40 – Introduction to Neural Computation	Computational neuroscience	4–5	Modeling neurons and learning rules
9	9.66J – Computational Cognitive Science	Cognitive modeling	4–5	Probabilistic reasoning, human-like perception
10	9.85 – Infant and Adult Cognition	Learning and development	2–3	Developmental and reinforcement models

Reading scientific pages on Kindle

When reading science (math) pages, the large screen (2K or 4K) is the best,

but I would like to have the whole library of papers in my pocket on Kindle.

I can send via email a PDF of any page to Kindle, but the PDF reading on a small Kindle device is awful. 

The same on Kindle Scribe might be a bit better, but in the end, I want font-scalable ePub.

Let's take an example from the following Wikipedia page as it has nice mathematics:

https://en.wikipedia.org/wiki/Spherical_coordinate_system

Pretty much every tool I have tried does convert HTML but fails to convert the math,

in-line LaTEX math seems to work fine, 

but the vector-graphic .svg does not:

I do have to consider that MAYBE it is the viewer that does not display Vector Graphics (.svg)!

Here is a list of tools I have tried:

WebToEpub Chrome extension

• Shows tables nicely
• shows images nicely
• converts LaTEX math YES
• SVG NO, shows them as "?", it might be the viewer's problem, I tried a few
• Calibre E-book viewer
• Kindle 7-inch 2022
• Apple Books
• Apple Preview - does not open ePub

EpubPress

• Creates a table of Contents with each Web page included, useless if converting a single page
• fails to convert table borders
• converts LaTEX fine
• drops (does not display) the Vector Graphics (.svg) 

dotEpub

• in the non-immerse mode, you can view the first few images only
• results in an error on Apple books
• fails to convert table borders
• converts LaTEX math YES
• on Kindle: SPELLS OUT the SVG formula, not good.
• in Calibre E-book viewer shows SVG nicely!

Summary 

1. Use print-to-PDF and view it in MacOS Preview on a big screen
2. If you read a long MATH and NO-image page, use dotEpub and read in the Calibre E-book viewer
3. If you want images, but you do not care for SVG math, WebTOEpub is best.

Sorry, no winning here.

View Kindle Scribe on Amazon: https://amzn.to/4db51Q7

Computational Mathematics

 

https://www.coursera.org/learn/uol-cm1015-computational-mathematics/supplement/Ok8Zg/introduction-to-computational-mathematics-course

handle numbers in any base and perform operations with binary numbers. You will learn about sequences, recursion and series, basic trigonometry and geometry.

You will also be introduced to functions, their different types, how to plot them and how to study their properties through basic calculus, limits and derivatives. You will also be introduced to linear algebra, vector spaces and the basic concepts of combinatorics, statistics and probability.

How to pass?

https://www.coursera.org/learn/uol-cm1015-computational-mathematics/supplement/57Ggy/how-to-pass-the-course

Number Bases

https://www.coursera.org/learn/uol-cm1015-computational-mathematics/lecture/nPHpG/introduction-to-number-bases-conversion-to-decimal

For any number base b, written with positions n such as:

$$ a_n a_{n-1} a_{n-2} ... a_0 $$

the conversion to decimal will be:

$$ a_n * b^n +  a_{n-1}* b^{n-1} + ... +  a_0*b^0 $$

Binary

• 0 - 00000000 
• 1 - 00000001 
• 2 - 00000010 
• 3 - 00000011 
• 4 - 00000100 
• 5 - 00000101 
• 6 - 00000110 
• 7 - 00000111 
• 8 - 00001000

$ 1001_2 \\ = 1*2^3 + 0*2^2 + 0*2^1 + 1*2^0  \\ = 8 + 0 + 0 + 1 \\ =  9_{10} $

$ 100 101 011_2 = \\
= 1*2^8 + 0*2^7 + 0*2^6 + 1*2^5 + 0*2^4 + 1*2^3 + 0*2^2 + 1*2^1 + 1*2^0 = \\
= 1*256 + 0*128 + 0*64 + 1*32 + 0*16 + 1*8 + 0*4 + 1*2 + 1*1 = \\
= 256 + 32 + 8 + 2 +1 = \\ = 299_{10} $

Decimal

count to 9, then zero add 1 in front to make 10. and so on

$ 127_{10} \\ = 100 + 20 + 7 \\ = 1*10^2 + 2*10^1 + 7*10^0 $

Hexadecimal (base 16)

0, 1, 2, ..., 9, A, B, C, D, E, F

$ 1F_{16} =  1*16^1 + 15*16^0 =  16 + 15 =  31_{10} $

Sexagesimal

 - Sumerians, Babylonians, angles, time, etc.


Method of repeated division

Special Characters used for Math, ML, Logic in Jupyther Lab

Here is a quick cheat sheet of useful Unicode characters you can use in Jupyther Lab and Julia language:

Greek Alphabet

α    \alpha
β    \beta
γ    \gamma
∇    \delta

ϵ    \epsilon

ζ    \zeta

η    \eta

θ    \theta

ι    \iota

κ    \kappa (should look like 'k')
λ    \lambda
μ    \mu

ν    nu (not supported in Jupyther)

ξ    \xi 

ο    omnicron (not supported in Jupyther)

π    \pi

ρ    \rho 

σ    \sigma

τ    \tau

υ    upsilon (not supported in Jupyther)

ϕ    \phi

χ    \chi

ψ    \psi

ω    \omega

Hebrew

ℵ    \aleph wiki

Machine Learning

x̂    x\hat

Math

∡    \measuredangle
∑    \sum
±    \pm (plus minus)

≠    \ne

≥    \ge (greater or equal)

≤    \le (less or equal)
⌀    \diameter
0°    0\degree 

Sets

∈    \in

Logic

∴    \therefore

⊻    \xor