Develop essential physical sciences skills with expert instruction and practical examples.
This course is designed to take you from a beginner to a confident practitioner in Python programming, image processing, and machine learning. Through step-by-step lessons and hands-on projects, you will build a solid foundation in these essential skills and apply them to real-world problems. What You'll Learn:Python Programming: Master Python basics, including data types, variables, loops, conditional statements, and libraries like NumPy and Matplotlib.
Image Processing: Learn how to process digital images using Python, including convolution operations, edge detection, and filters. Machine Learning: Gain a strong understanding of core ML concepts, including Linear and Logistic Regression, with practical coding examples. Deep Learning and CNNs: Build neural networks from scratch, train them using TensorFlow and Keras, and explore convolutional neural networks (CNNs).
Hands-on Projects:You'll work on engaging projects such as:Analyzing real astronomical image datasets like NGC3184 and M87. Building and training machine learning models for classification and regression tasks. Implementing neural networks and CNNs to solve real-world problems using Kaggle datasets.
Who This Course Is For:Beginners with no prior experience in Python or machine learning. Students and professionals looking to strengthen their knowledge of AI and data science. Anyone interested in exploring how programming and AI are applied to real-world scenarios, such as image processing and astronomy.
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