𝟏. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐚𝐧𝐝 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐔𝐬𝐢𝐧𝐠 𝐏𝐲𝐭𝐡𝐨𝐧
– A Notion of computation
– The Python programming language
– Some simple algorithms
– Testing and debugging
– An informal introduction to algorithmic complexity
– Data structures
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𝟐. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐚𝐧𝐝 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞
– Advanced programming in Python 3
– Dynamic programming
– Plotting with the pylab package
– Random walks
– Probability, Distributions
– Monte Carlo simulations
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3. 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐂𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧
– Techniques for software development
– Software testing
– Design patterns
– Functional programming
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4. 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐏𝐲𝐭𝐡𝐨𝐧: 𝐟𝐫𝐨𝐦 𝐋𝐢𝐧𝐞𝐚𝐫 𝐌𝐨𝐝𝐞𝐥𝐬 𝐭𝐨 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
– Classification, regression, clustering, and reinforcement learning
– Linear models, neural networks, and graphical models
– Implement and organize machine learning projects
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5. 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
– Model, form hypotheses, perform statistical analysis
– Use dimension reduction techniques such as principal component analysis – Visualize high-dimensional data
– Model time series using moving average
– Use Gaussian processes to model data
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