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
Materials
- 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.
Downloading
- All notebooks can be downloaded from HERE.
Calculus 1
| 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 |
Calculus 2
| 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 |
Linear Algebra
| 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 |
Discrete Math
| 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 |