Beginner Guide to Artificial Intelligence & Machine Learning

About this course

Implement Machine Learning algorithmsHow to improve your Machine Learning ModelsBuild a portfolio of work to have on your resumeSupervised and Unsupervised LearningExplore large datasets using data visualization tools like Matplotlib Learn NumPy and how it is used in Machine LearningLearn to use the popular library Scikit-learn in your projectsLearn to perform Classification and Regression modellingMaster Machine Learning and use it on the jobLearn which Machine Learning model to choose for each type of problemLearn best practices when it comes to Data Science WorkflowLearn how to program in Python using the latest Python 3Learn to pre process data, clean data, and analyze large data.Developer Environment setup for Data Science and Machine LearningA portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks providedReal life case studies and projects to understand how things are done in the real worldGuidance to choose your career path based on your background and build the path in next 6 monthsComprehensive understanding on foundational concepts like Neurons, Perceptron, Multilayer Perceptron, Transformers. Good overview on Convolution Neural Networks and Recurrent Neural Networks