This Artificial Intelligence Master's program includes 5+ real-life, industry-based projects on different domains to help you master concepts of Artificial Intelligence like Supervised Learning, Unsupervised Learning, Reinforcement Learning, Support Vector Machines, Deep Learning, TensorFlow, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks. A few of the projects, that you will be working on are mentioned below:
Description: You will go through dedicated mentored classes in order to create a high-quality industry project, solving a real-world problem leveraging the skills and technologies learnt throughout the program. The capstone project will cover all the key aspects from exploratory data analysis to model creation and fitting. As a learner, you will cover cutting edge AI-based supervised and unsupervised algorithms like Regression, Multinomial Naïve Bayes, SVM, Tree-based algorithms, NLP, etc. You also get the option of choosing the domain/industry dataset you to want to work on from the options available. After successful submission of the project, you will be awarded a capstone certificate that can be showcased to potential employers as a testament to your learning.Project 1: Predicting house prices in California
Domain: Machine Learning
Description: Build a model that predicts median house values in California districts, given metrics such as population, median income, median housing price, etc for each block group in California
Project 2: Learn how Stock Markets like NASDAQ, NSE, BSE, leverage on Artificial Intelligence and Machine Learning to arrive at a consumable data from complex datasets
Domain: Stock Market
Description: As a part of the project, you need to import data using Yahoo data reader of the following companies: Yahoo, Apple, Amazon, Microsoft, and Google. Perform fundamental analytics including plotting closing price, plotting stock trade by volume, performing daily return analysis, and using pair plot to show the correlation between all the stocks.
Project 3: See how Artificial Intelligence and Data Science is used in the field of engineering by taking up this case study of MovieLens Dataset Analysis.
Description: The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The researchers of this group are involved in many research projects related to the fields of information filtering, collaborative filtering, and recommender systems.
Project 4: Learn how leading Healthcare industry leaders make use of Artificial Intelligence and Data Science to leverage their business.
Domain: Health Care
Description: Predictive analytics can be used in healthcare to mediate hospital readmissions. In healthcare and other industries, predictors are most useful when they can be transferred into action. But historical and real-time data alone are worthless without intervention. More importantly, to judge the efficiency and value of forecasting a trend and ultimately changing behaviour, both the predictor and the intervention must be integrated back into the same system and workflow where the trend originally occurred.
Project 5: Understand how the Insurance leaders like Berkshire Hathaway, AIG, AXA, etc make use of Artificial Intelligence by working on a real-life project based on Insurance.
Description: Use of predictive analytics has increased greatly in insurance businesses, especially for the biggest companies, according to the 2013 Insurance Predictive Modelling Survey. While the survey showed an increase in predictive modelling throughout the industry, all respondents from companies that write over $1 billion in personal insurance employ predictive modelling, compared to 69% of companies with less than that amount of premium.
Project 6: See how banks like Citigroup, Bank of America, ICICI, HDFC make use of Artificial Intelligence to stay ahead of the competition.
Description: A Portuguese banking institution ran a marketing campaign to convince potential customers to invest in a bank term deposit. Their marketing campaigns were conducted through phone calls, and sometimes the same customer was contacted more than once. Your job is to analyze the data collected from the marketing campaign.