Machine Learning
Machine Learning course, participants will embark on a comprehensive exploration of the field, starting with foundational concepts such as data preprocessing, feature engineering, and model evaluation. The course delves into both supervised learning, where models learn from labeled data, and unsupervised learning, uncovering patterns in unlabeled data.
Prerequisites:
Basic knowledge of software development and system administration concepts.
Course Duration:150 hours
Upon completion of this course, students will:
Moreover, the course emphasizes ethical considerations, addressing the responsible development and deployment of ML models. Topics such as bias and fairness in machine learning are discussed to foster an understanding of the societal impact of AI technologies. Throughout the program, participants engage in practical projects, applying their knowledge to solve problems and gain valuable experience. By the end of the course, learners will be well-equipped to navigate the diverse landscape of Machine Learning, from model development to ethical considerations and deployment strategies.