Program Prerequisites

Master Data Science & AI

This program is designed for both working professionals and students who are in the third year of college and higher. If you are willing to invest time and effort into becoming an expert in AI or DSE, you should apply. The program requires prior experience in Python programming, and Python libraries such as numerical python (NumPY) and Pandas. The program also requires you to be familiar with basic (high-school or first-year of college level) linear algebra and statistics. If you do not meet these prerequisites, then look up our 5-week Foundations Program.

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Accelerated AI & DSE

This program is ideal for those seeking opportunities in Machine Learning and AI, as well as programmers, engineers, and project managers seeking to take their skills to the next level. This program is designed for both working professionals and students who are in the third year of college and higher. The program requires prior experience in Python programming, and the Python libraries - NumericalPython (NumPY) and Pandas. The program also requires you to be familiar with basic (high-school or first-year of college level) linear algebra and statistics. If you do not meet these prerequisites, then look up our 5-week Foundations Program.

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Advanced AI

This program is designed for both working professionals and students who have already mastered the basics of AI. It is expected that you be familiar with the basics of Neural Networks including Convolutional and Recurrent Networks before starting this program. If you think you meed additional preparation prior to taking this program, please enrol in our AI-1 (starts September 15, 2020) and AI-2 (starts November 1, 2020) modules on a stand-alone basis.

  • Probability, probability distributions, maximum likelihood, and loss
  • kNN, Linear regression, logistic regression
  • complexity, regularization with polynomial regression, bayes loss
  • Classification, classification metrics, feature selection
  • Metrics and data imbalance, ROC curves, Precision, and Recall
  • Multi Layer perceptrons and Backpropagation
  • Optimizers
  • Dropout and Batch Normalization. Initialization methods.
  • Convolutional Neural Networks and Data Augmentation
  • Convolutional Architectures and interpretation
  • Transfer Learning: use models pre-trained by others and customize them for your data set
  • Batch Normalization and Resnets
  • Basic Code First Autoencoders and encoder decoder networks
  • Variational Autoencoders
  • An introduction to GANs
  • Recurrent Neural networks, GRU, LSTM
  • Using language embeddings
  • Language modelling using Recurrent Networks
  • Transfer Learning for Language

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Advanced DSE

This program is designed for both working professionals and students who have already mastered the basics of Data Science. It is expected that you be familiar with the basics of data science before starting this program. If you think you need additional preparation prior to taking this program, please enrol in our DS-1 (starts January 1, 2021) and DS-2 (starts February 15, 2021) modules on a stand-alone basis.

  • http, APIs, scraping
  • Text parsing with regex and other methods
  • Simple machine learning pipelines and data leakage
  • More pandas, and sql.
  • Post modeling visualization, best practices, and communication
  • Exploratory data analysis and visualization
  • PCA and unsupervised learning
  • Querying, Embeddings and Similarity, MLPs for tabular data
  • SGD, collaborative filtering, and recommendation systems
  • Generative models such as LDA and naive bayes
  • Clustering and k-means
  • Basic bayesian modeling and hierarchical thinking
  • SVM, the hinge loss, and kernel models
  • Decision trees
  • Bootstrap and bagging, random forests
  • Boosting
  • Data imbalance and decision making in the context of the above models
  • Model interrogation and visualization

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AI-1: Basics of AI & ML

If you are someone who would like learn at your own pace, we make individual modules available for enrolment. We recommend that you take both AI-1 and AI-2 to round out your basic training in AI. With both these modules completed, you will have completed all the prerequisites necessary to take the Advanced Program in AI at a later date. The program requires prior experience in Python programming, and python libraries such as NumPY and Pandas. The program also requires you to be familiar with basic (high-school or first-year of college level) linear algebra and statistics. If you do not meet these prerequisites, then look up our 5-week Foundations Program.

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