Upon completion of this program, candidates should be able to:
• Build artificial neural networks with Tensorflow and Keras
• Classify images, data, and sentiments using deep learning
• Make predictions using linear regression, polynomial regression, and multivariate regression
• Data Visualization with MatPlotLib and Seaborn
• Implement machine learning at massive scale with Apache Spark’s MLLib
• Understand reinforcement learning – and how to build a Pac-Man bot
• Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naïve Bayes, and PCA
• Use train/test and K-Fold cross validation to choose and tune your models
• Build a movie recommender system using item-based and user-based collaborative filtering
• Clean your input data to remove outliers
• Design and evaluate A/B tests using T-Tests and P-Values
• Developers aspiring to be an Artificial Intelligence Engineer or Machine Learning Engineer
• Analytics Managers who are leading a team of analysts
• Information Architects who want to gain expertise in Artificial Intelligence algorithms
• Analytics professionals who want to work in machine learning or artificial intelligence
• Graduates looking to build a career in Artificial Intelligence and machine learning
• Experienced professionals who would like to harness Artificial Intelligence in their fields to get more insight
You'll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer.
The course will walk you through installing the necessary free software.
• Some prior coding or scripting experience is required.
• At least high school level math skills will be required.