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Full Stack Data Science Program

This is the most comprehensive Full Stack Data Science program available that covers all steps of the Data Science process, from Data Integration, Data Manipulation, Descriptive Analytics and Visualization to Statistical Analysis, Predictive Analytics, and Machine Learning models using R, Python, Tableau, Tensor Flow, and Keras.

Learning Python with PyCharm (Linkedin Learning)

Get your development environment set up correctly with instructor Bruce Van Horn's step-by-step guidance, and explore PyCharm's first-rate text editing tools. Learn how to improve your code quality with Lens Mode and Intentions, refactor and debug code, and perform unit testing with the PyCharm test runner.

Python Essential Training (Linkedin Learning)

In this course, Bill Weinman demonstrates how to use Python 3 to create well-designed scripts and maintain existing projects. This course covers the basics of the language syntax and usage, as well as advanced features such as objects, generators, and exceptions.

R for Data Science: Lunchbreak Lessons (Linkedin Learning)

Programming is learned in small bits. You build on basic concepts. You transfer the knowledge you already have to the next language. Lunch Break Lessons teaches one of the most popular programming languages for data analysis and reporting'in short lessons that expand on what existing programmers already know.

R: Interactive Visualizations (Linkedin Learning)

Start by learning to manage packages and structure data for visualizations with the tidyverse and the pipe operator. Then there is an important question: Which library should you choose? The course introduces five popular options: Leaflet, Plotly, Highcharter, visNetwork, and DataTables (DT).

Learning From Data

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications.

Deep Learning Crash Course

In this liveVideo course, machine learning expert Oliver Zeigermann teaches you the basics of deep learning. With Oliver Zeigermann's crystal-clear video instruction and the hands-on exercises in this video course, you'll get started in deep learning using open-source Python-friendly tools like scikit-learn and Keras, and TensorFlow 2.0 (soon to be officially released with exciting new updates!).

Keras in Motion

Keras in Motion teaches you to build neural-network models for real-world data problems using Python and Keras. In over two hours of hands-on, practical video lessons, you'll apply Keras to common machine learning scenarios, ranging from regression and classification to implementing Autoencoders and applying transfer learning.

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