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Machine Learning for Software Engineers

Machine Learning for Software Engineers

If you're a software engineer looking to add Machine Learning to your skillset, this is the place to start.

This course will teach you to write useful code and create impactful Machine Learning applications immediately. From the start, you'll be given all the tools that you need to create industry-level machine learning projects. Rather than reading through dense theory, you’ll learn practical skills and gain actionable insights. 

Topics covered include data analysis/visualization, feature engineering, supervised learning, unsupervised learning, and deep learning. All topics are taught with industry standard frameworks: NumPy, pandas, scikit-learn, XGBoost, TensorFlow, and Keras.

Basic knowledge about Python is a prerequisite to this course.

This course was created by AdaptiLab, a company specializing in evaluating, sourcing, and upskilling enterprise machine learning talent. It is built in collaboration with industry machine learning experts from Google, Microsoft, Amazon, and Apple.

Add machine learning to your skillset and equip yourself to push the boundaries of AI technology. Get the hands-on practice you'll need to land a job in ML.

Machine Learning skills are some of the most sought-after in the modern job market. Modern ML Engineers make dozens of thousands of dollars more per year than other developers. This path will teach you the essential ML techniques to stand out from the competition. By the end, you'll have job-ready skills in data pipeline creation, model deployment, and inference.

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