Machine Learning & Artificial Intelligence

Machine Learning is the technology behind some of the most exciting innovations today. Self-driving cars, voice-controlled personal assistance, AI to help doctors diagnose diseases: All of these were developed with the help of Machine Learning software engineers.

Students will learn from the ground up all of the pieces necessary to build machine learning models using everything from Numpy, and Tensorflow, to Keras and apply them to real-world situations for application to future professional experiences of students.

Students will learn to build out the forward and back-propagation of deep feed-forward, convolutional, and recurrent neural networks. They will also learn about databases, how to scrape and label datasets while avoiding human bias, how to manage large-scale datasets, and about both data collection and management. Graduates in this program can reasonably expect to get jobs as Machine Learning Engineer, AI Engineer, Data Engineer, Data Scientist, Data Analyst, Big Data Developer, Machine Learning Infrastructure Developer, Python Developer, Tensorflow Developer.

1ST TRIMESTER

Advanced Python

2ND TRIMESTER

– Linear Algebra
– Calculus
– Probability
– Classification
– Regularization
– Optimization
– Error Analysis
– Convolutional Neural Network
– Deep Convolutional
– Architectures
– Transfer Learning
– Object Detection
– Face Verification
– Neural Style Transfer

3RD TRIMESTER

– Advanced Probability
– Advanced Linear Algebra
– Recurrent Neural Networks
– Deep Recurrent Architectures
– Natural Language Processing
– Time Series Analysis
– Dimensionality Reduction
– Clustering
– Hidden Markov Models
– Neural Style Transfer

4TH TRIMESTER

– Multi-armed Bandit
– Epsilon Greedy
– Deep Reinforcement Learning
– Bias Avoidance
– Pandas
– RESTful APIs
– MapReduce
– SQL and NoSQL Databases
– Google Cloud Platform
– Hadoop
– Learning Project of Your Choice