Math with Application at MSA Uni.

Best Student Project

Predictive Population Model By Eyad Magdy, A rising freshman (1st year) student.
Before completing Programming I, He learned Python, and made a practical project.
Before completing Calculus I, He learned partial derivatives and implemented the gradient descent algorithm, to train a linear model.
He well explains the case-study motivation, population growth prediction, behind his algorithm and analytics.
Github Source Code, Hugging Face Deployed Model

Briggs, Cochran, Gillett & Schulz. Calculus for Scientists and Engineers, Early Transcendentals. Pearson.
Kolman & Hill. Elementary Linear Algebra With Applications. Pearson.
Rosen. Discrete Math and its Applications. McGraw Hill.

Week	On-Paper	Python & Programming	Frameworks	Project & Case-study
Week 00	0.1 - Intro.ipynb, 0.2 - Preliminaries.ipynb	0 - Intro to Python & Colab.ipynb	0.1 - Intro.ggb
Week 01	1 - Functions_ Graphing, Exponential, Logarithmic.ipynb	1 - List Comprehension.ipynb	1 - Sequence, Function on sequence, Graphing.ipynb	1 - Airlines & Product management profit prediction.ipynb
Week 02	2 - Functions_ Odd, Even, Shifting, Scaling.ipynb	2 - Shifting & Scaling a List.ipynb	2 - Shifting & Scaling a Sequence.ipynb	2 - Maximizing Car Renting Revenue.ipynb
Week 03	3 - Inverse Functions.ipynb	3 - Inverting lists, Find max_min by looping.ipynb	3 - Grahping Inverse Functions.ipynb	Optimization by Gradient Descent.ipynb, ECommerce_consumer_behaviour.csv, real_estate.csv
Week 04	4 - Continuity & Limits.ipynb	4 - Table of values for rate of change.ipynb	4 - Plotting Tangent.ipynb
Week 05	5 - Differentiation_ Properties & Chain.ipynb	5 - While command.ipynb
Week 06	6 - Differentiation_ First & Higher.ipynb	6 - Appending to List.ipynb
Week 09		9 - 2d list.ipynb	9 - Dataset Manipulation.ipynb
Week 10	10 - L_Hopital.ipynb		10 - Sampling.ipynb
Week 11	11 - Rules of Integration.ipynb
Week 12	12 - Definite & Indefinite.ipynb
Week 13	13 - Integration by Substitution & by Parts.ipynb
Week 14	Tutorial sheet.pdf

Week	On-Paper	Python & Programming	Frameworks	Project & Case-study
Week 00	0.1 - Intro.ipynb, 0.2 - Preliminaries.ipynb	0.3 - Python & Colab.ipynb
Week 01	1 - Riemann Sum.ipynb	1 - List Comprehension, Riemann Sum.ipynb	1 - Trapezoidal.ipynb	1 - Profit for a Segment.ipynb
Week 02	2 - Definite & Indefinite.ipynb	2 - Compute area under the curve.ipynb	2 - Plot area under curve.ipynb, 2 - Total profit & Maximizing revenue.ipynb
Week 03	3 - Integration by Substitution.ipynb	3 - Table of values.ipynb	3 - Visualizing Functions.ipynb	Multi-variable Gradient Descent.ipynb, customer_order_hour_infRate.csv, ECommerce_consumer_behaviour.csv, real_estate.csv
Week 04	4 - Integration by Parts.ipynb	4 - While command.ipynb	4 - multivariable-gradient.ggb
Week 05	5 - Trigonometric Integration & Substitution.ipynb
Week 06	6 - Partial Fraction Integration.ipynb
Week 09	9 - Partial Derivatives & Chain.ipynb		9 - Manipulating dataset.ipynb
Week 10	Differential Equations.ipynb		10 - Sampling.ipynb
Week 11	11 - Power Series and Tests of Convergence.ipynb
Week 12	Tutorial sheet.pdf
Week 13
Week 14

Week	On-Paper	Python & Programming	Frameworks	Project & Case-study
Week 00	0.1 - Intro.ipynb, 0.2 - Preliminaries.ipynb	0 - Intro to Python & Colab.ipynb
Week 01	1 - Matrix Algebra.ipynb	1 - List comprehension & 2d matrix addition.ipynb	1 - Matrix Algebra.ipynb	1 - Travel cost.ipynb
Week 02	2 - Solving Linear Systems.ipynb	2 - Elementary Matrix Operations.ipynb	2 - Solving a system.ipynb	2 - Finding Bills Number.ipynb
Week 03	3 - Determinants.ipynb	3 - Inversion Count.ipynb	3 - Computing the Determinant.ipynb
Week 04	4 - Cramer.ipynb	4 - Matrix Multiplication.ipynb	4 - Matrix Algebra on Geogebra.ipynb	4 - Business, Real-data, Business Modeling.ipynb, Spotify_data.xlsx, filmtv_movies.csv
Week 05	5 - Matrix Inverse.ipynb		5 - Sublist, Functional min_max and sorting.ipynb	5 - Cosine Similarity.ipynb
Week 06	6 - Vector Space.ipynb	6 - List Comprehension.ipynb		6 - Euclidean Distance & Centroids.ipynb
Week 09	9 - Span, Independence, Basis, Dimension.ipynb		9 - Boolean Indexing & Recursion.ipynb	9 - Collaborative Filtering.ipynb
Week 10			10 - Pandas, selecting, NULLs, conversion to numpy.ipynb	10 - Movielens Dataset.ipynb, movies.csv, user-movie-rating.csv
Week 11			11 - Sampling.ipynb	11 - Sampling.ipynb
Week 12	12 - Eigenvalues & Eigenvectors.ipynb			12 - Evaluation by Precision & Recall.ipynb
Week 13	13 - Similar Matrices.ipynb
Week 14

Week	Notebook
Week 00	0.1 - Intro.ipynb, 0.3 - Python & Colab.ipynb
Week 01	1 - Intro to Logic.ipynb
Week 02
Week 03	3 - Logical Equivalence.ipynb
Week 04
Week 05	5 - Structures.ipynb
Week 06
Week 09	9 - Graphs, Algorithms, Recurrence.ipynb
Week 10
Week 11	11 - Recursive Algorithms.ipynb
Week 12	12 - Project Progressive Hints.ipynb
Week 13	13 - Project Graph Components by Recursion.ipynb
Week 14