Your programming toolbox wouldn’t be complete without Python. Whether you’re looking to work in data analysis, machine learning, or web development, this course walks you through using Python to solve a myriad of programming problems. You’ll dive into Python loops, data structures, functions, and more to help you perform basic programming tasks and confidently apply those skills to real-world scenarios.
- Access 28 lectures & 3 hours of content 24/7
- Get started w/ zero Python experience
- Enhance your understanding of loops, data structures, functions & classes
- Explore popular Python libraries & Web scraping
- Discover what it takes to write a real Python app
Work as a deep learning developer would be infinitely harder without TensorFlow. Created by Google in 2015, this open-source software library makes it easier for developers to design, build, and train deep learning models. Using TensorFlow, this course will guide you through Convolutional Neural Networks and Recurrent Neural Networks, cutting-edge tools in image recognition, language modeling, and working with high-frequency data.
- Access 28 lectures & 3.5 hours of content 24/7
- Use TensorFlow to work w/ convolutional & recurrent neural networks
- Learn how neural networks contribute to image recognition & language modeling
- Explore real-world deep learning examples via lab lessons
Deep learning has allowed today’s AI applications to do some amazing things, but only the Cloud has enough computing firepower to keep these programs running. This course will guide you through running deep learning models in TensorFlow on the Google Cloud platform. You’ll explore building and deploying TensorFlow models and apply your skills to the real world with a taxicab fare prediction problem.
- Access 30 lectures & 3 hours of content 24/7
- Learn how to build & deploy TensorFlow models on Google Cloud
- Refine your training w/ real-world labs, like a taxicab fare prediction problem
- Explore feature engineering & hyperparameter tuning
Unsupervised deep learning might sound chaotic, but there’s a method to the madness. While supervised deep learning hinges on the programmer telling the program which insights to find, unsupervised deep learning allows the machine to gather insights on its own, making for unique—and sometimes game-changing—discoveries. Make your way through this training, and you’ll explore the theory of unsupervised deep learning and implement models in TensorFlow.
- Access 22 lectures & 2.5 hours of content 24/7
- Discover how to implement unsupervised deep learning models w/ TensorFlow
- Learn the advantages of supervised versus unsupervised deep learning
- Explore K-means clustering w/ images
- Understand how to create & work on a datalab instance
Deep learning isn’t just about helping computers learn from data—it’s about helping those machines determine what’s important in those datasets. This is what allows for Tesla’s Model S to drive on its own and for Siri to determine where the best brunch spots are. Using the machine learning workhorse that is TensorFlow, this course will show you how to build deep learning models and explore advanced AI capabilities with neural networks.
- Access 62 lectures & 8.5 hours of content 24/7
- Understand the anatomy of a TensorFlow program & basic constructs such as graphs, tensors, and constants
- Create regression models w/ TensorFlow
- Learn how to streamline building & evaluating models w/ TensorFlow’s estimator API
- Use deep neural networks to build classification & regression models
If you’re at all interested in the technology that powers Siri, self-driving cars, and other AI innovations, you’ll need to get comfortable with machine learning. This course features training from Silicon Valley pros with decades of experience under their belts. Even if you’ve never touched a line of code before, these experts will help you put Machine Learning and Python into action and harness a new level of programming power.
- Access 38 lectures & 8.5 hours of content 24/7
- Get introduced to Machine Learning
- Learn from a team w/ decades of practical experience in quant trading, analytics & e-commerce
- Understand complex programming subjects w/ the help of animations
- Discover how to implement natural language processing & machine learning for text classification in Python
Classification models play a key role in helping computers accurately predict outcomes, like when a banking program identifies loan applicants as low, medium, or high credit risks. This course offers an overview of machine learning with a focus on implementing classification models via Python’s scikit-learn. If you’re an aspiring developer or data scientist looking to take your machine learning knowledge further, this course is for you.
- Access 17 lectures & 2 hours of content 24/7
- Tackle basic machine learning concepts, including supervised & unsupervised learning, regression, and classification
- Learn about support vector machines, decision trees & random forests using real data sets
- Discover how to use decision trees to get better results
From suggested Facebook friends to recommended videos on Netflix, it’s scary how accurate these systems can be; but they’re not powered by magic. This course peels back the curtain on the technology that drives these programs. Using Python, you’ll discover what goes into designing and implementing recommendation systems and explore the different ways they curate content.
- Access 20 lectures & 4 hours of content 24/7
- Identify use-cases for recommendation systems
- Design & implement recommendation systems in Python
- Discover the different means of filtering content
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