Build a stronger understanding of foundational machine learning by using Python. This online course is designed for professionals looking to upskill as well as students and job seekers interested in learning the fundamentals of machine learning applications and data mining in Python. Skills gained in the course can be used across a broad array of industry roles, including marketing, business analytics, data analytics, and web and Python programming. 

Through online lectures, interactive assignments and projects, you’ll develop practical applications such as search engines, image analysis, bioinformatics, industrial automation, speech recognition and more. Examine machine learning concepts, gain a basic understanding of supervised machine learning and Bayesian classifiers, learn concepts in unsupervised machine learning and clustering algorithms and apply neural networks to machine learning. 

Learning Outcomes 

• Identify and formulate machine learning problems using Python 
• Understand and implement algorithms to solve simple machine learning problems 
• Analyze the performance of machine learning solutions on practical datasets 

Skills You’ll Gain 

• Usage of histograms for supervised machine learning and Bayesian classifiers  
• Design and application of classifiers like k-nearest neighbors, linear machines and decision trees  
• Unsupervised machine learning and cluster algorithms such as expectation maximization and k-means clustering