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The “Machine Learning with Python for Managers” course is created to introduce managers and business professionals to the basic concepts and practical applications of machine learning, with Python as the main programming language. Throughout the 12-week course, participants will acquire theoretical knowledge and practical experience required to seamlessly incorporate machine learning techniques into their business strategies. The course starts by establishing a solid understanding of machine learning concepts and covers important types of machine learning, like supervised and unsupervised learning. Students will investigate how these techniques can be applied in various fields. Additionally, they will develop an acquaintance with Python, with a focus on its fundamental syntax, data types, and essential libraries such as NumPy, Pandas, and Matplotlib, which are crucial for data manipulation and visualization. As the course progresses, students will explore various data preparation techniques, including data preprocessing, exploratory data analysis, and feature engineering. These techniques are crucial for developing effective machine learning models. The course will cover supervised learning models like regression and classification, providing insight into how these algorithms can be used to address business challenges such as sales forecasting and customer segmentation. Additionally, participants will be introduced to unsupervised learning techniques like clustering, which will help them grasp the concepts of data grouping and segmentation. The course covers model evaluation, optimization, and time series forecasting. It includes ARIMA and SARIMA models with real-world applications such as stock price prediction. By the end of the course, learners will explore practical applications of machine learning in domains like marketing, finance, and human resources. This will equip learners with the skills to apply machine learning models in decision-making processes, improving business performance and strategy development.
