Data

Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries

Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes

Unleash the power of Python libraries like Gensim, NLTK, SpaCy, and Keras to solve common and not-so-common challenges faced in the NLP domain.

Applied machine learning with a solid foundation in theory. Revised and expanded with TensorFlow 2, GANs, and reinforcement learning.

Acquire necessary skills in preparing for Microsoft certification and enhance your software development career by learning the concepts of C# programming

Perform advanced data manipulation tasks using pandas and become an expert data analyst.

Build automated and highly-scalable end-to-end Machine Learning models and pipelines in Azure using Tensorflow, Spark, and Kubernetes.

Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization

Understand the fundamentals of algorithmic trading to apply algorithms to real market data and analyze the results of real-world trading strategies

Use Java and Deeplearning4j to build robust, scalable, and highly accurate AI models from scratch

Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python

Take your enterprise application development skills to the next level by mastering parallel programming techniques in .NET and C#.

Build powerful deep learning models using fewer learning samples with the power of scikit-learn and Keras

Learn the essential background and model functioning of various neural network architectures such as CNN. RNN. LSTM, GANs, Autoencoders and more using best practices from an industry expert

Your one-stop guide to working with the browser-based JavaScript library for training and deploying machine learning models effectively.