Machine Learning for Business using python

Course Description

The Machine Learning for Business using Python course provides a comprehensive overview of the fundamentals and applications of machine learning in business. This course is designed to provide students with the necessary knowledge and skills to enable them to implement machine-learning projects successfully. The course covers topics such as supervised and unsupervised learning, data preprocessing, feature engineering, model selection, hyperparameter optimization, validation techniques, deep learning models, natural language processing (NLP), reinforcement learning algorithms, time series forecasting methods and more. The course may also include hands-on projects and case studies to give students practical experience in using machine learning in a business setting. By the end of this course, you will have acquired essential practical skills in applying cutting-edge AI technology to solve real-world problems in business

Learning Outcomes

At the end of this course, learners will gain the ability to:

1. Understanding of supervised and unsupervised machine learning techniques and how they can be applied to business problems
2. Familiarity with Python libraries such as scikit-learn, TensorFlow, and Keras for implementing machine learning models
3. Ability to perform data pre-processing and feature engineering for machine learning tasks
4. Knowledge of common evaluation metrics and how to interpret the results of machine learning models
5. Understanding of how to implement and evaluate different types of models such as linear regression, decision trees, and neural networks
6. Hands-on experience with working on projects and case studies that demonstrate the application of machine learning in a business setting