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Guerrilla Guide from the NUKE Trenches. Over the years at fxphd, we've had a lot of great courses covering NUKE from a variety of perspectives. This term, we're going back to our roots with a course covering techniques that solve problems compositors run into every day on the job.

Practical and easy to understand, DATABASE SYSTEMS: DESIGN, IMPLEMENTATION, AND MANAGEMENT, Tenth Edition, gives readers a solid foundation in database design and implementation. Filled with visual aids such as diagrams, illustrations, and tables, this market-leading book provides in-depth coverage of database design, demonstrating that the key to successful database implementation is in proper design of databases to fit within a larger strategic view of the data environment. Renowned for its clear, straightforward writing style, the tenth edition has been thoroughly updated to include hot topics such as green computing/sustainability for modern data centers, the role of redundant relationships, and examples of web-database connectivity and code security. In addition, new review questions, problem sets, and cases have been added throughout the book so that readers have multiple opportunities to test their understanding and develop real and useful design skills.

Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning. It has now been updated and expanded to two parts for even more hands-on experience with Python. In this course, instructor Lillian Pierson takes you step by step through a practical data science project: building machine learning models that can generate predictions and recommendations and automate routine tasks. Along the way, she shows how to perform linear and logistic regression, use K-means and hierarchal clustering, identify relationships between variables, and use other machine learning tools such as neural networks and Bayesian models. You should walk away from this training with hands-on coding experience that you can quickly apply to your own data science