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Optimize TensorFlow Models For Deployment with TensorRT

Optimize TensorFlow Models For Deployment with TensorRT

This is a hands-on, guided project on optimizing your TensorFlow models for inference with NVIDIA's TensorRT. By the end of this 1.5 hour long project, you will be able to optimize Tensorflow models using the TensorFlow integration of NVIDIA's TensorRT (TF-TRT), use TF-TRT to optimize several deep learning models at FP32, FP16, and INT8 precision, and observe how tuning TF-TRT parameters affects performance and inference throughput.

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  • 3 hours
  • English
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Python: A Guided Journey from Introduction to Application

Python: A Guided Journey from Introduction to Application

In today’s society, uses for new technologies are broadening in scope and revolutionizing the world. Many new technologies automate redundant tasks so people may complete tasks of greater priority. These new automated technologies depend on the constant innovation of software. To develop software that can increase our efficiency and change the world for the better, it is vital to understand how to code using different programming languages.

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  • English
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Introduction to Portfolio Construction and Analysis with Python

Introduction to Portfolio Construction and Analysis with Python

The practice of investment management has been transformed in recent years by computational methods. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language.

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  • 25 hours
  • English
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Python Data Structures

Python Data Structures

This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Everybody”. This course covers Python 3.

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  • 3 hours
  • English
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Python for Genomic Data Science

Python for Genomic Data Science

This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.

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  • 9 hours
  • English
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Python Basics

Python Basics

This course introduces the basics of Python 3, including conditional execution and iteration as control structures, and strings and lists as data structures. You'll program an on-screen Turtle to draw pretty pictures. You'll also learn to draw reference diagrams as a way to reason about program executions, which will help to build up your debugging skills. The course has no prerequisites.

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  • 34 hours
  • English
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Python Programming Essentials

Python Programming Essentials

This course will introduce you to the wonderful world of Python programming! We'll learn about the essential elements of programming and how to construct basic Python programs. We will cover expressions, variables, functions, logic, and conditionals, which are foundational concepts in computer programming. We will also teach you how to use Python modules, which enable you to benefit from the vast array of functionality that is already a part of the Python language.

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  • 10 hours
  • English
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Customising your models with TensorFlow 2

Customising your models with TensorFlow 2

Welcome to this course on Customising your models with TensorFlow 2! In this course you will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow.

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  • 27 hours
  • English
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Computational Thinking for Problem Solving

Computational Thinking for Problem Solving

Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.

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  • 18 hours
  • English
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Getting started with TensorFlow 2

Getting started with TensorFlow 2

Welcome to this course on Getting started with TensorFlow 2! In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models using the Sequential API, validating your models and including regularisation, implementing callbacks, and saving and loading models. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant.

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  • 26 hours
  • English
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Programming in Python

Programming in Python

In this course, you will be introduced to foundational programming skills with basic Python Syntax. You’ll learn how to use code to solve problems. You’ll dive deep into the Python ecosystem and learn popular modules, libraries and tools for Python. You’ll also get hands-on with objects, classes and methods in Python, and utilize variables, data types, control flow and loops, functions and data structures.

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  • 45 hours
  • English
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Python Data Representations

Python Data Representations

This course will continue the introduction to Python programming that started with Python Programming Essentials. We'll learn about different data representations, including strings, lists, and tuples, that form the core of all Python programs. We will also teach you how to access files, which will allow you to store and retrieve data within your programs. These concepts and skills will help you to manipulate data and write more complex Python programs. By the end of the course, you will be able to write Python programs that can manipulate data stored in files.

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  • 9 hours
  • English
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Python Data Analysis

Python Data Analysis

This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs.

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  • 9 hours
  • English
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Introduction to Computer Vision and Image Processing

Introduction to Computer Vision and Image Processing

Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries, such as self-driving cars, robotics, augmented reality, and much more. In this beginner-friendly course, you will understand computer vision and learn about its various applications across many industries. As part of this course, you will utilize Python, Pillow, and OpenCV for basic image processing and perform image classification and object detection. This is a hands-on course and involves several labs and exercises.

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  • 22 hours
  • English
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Python Functions, Files, and Dictionaries

Python Functions, Files, and Dictionaries

This course introduces the dictionary data structure and user-defined functions. You’ll learn about local and global variables, optional and keyword parameter-passing, named functions and lambda expressions. You’ll also learn about Python’s sorted function and how to control the order in which it sorts by passing in another function as an input. For your final project, you’ll read in simulated social media data from a file, compute sentiment scores, and write out .csv files.

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  • 31 hours
  • English
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AI for Medical Diagnosis

AI for Medical Diagnosis

AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required!

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  • 20 hours
  • English
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The Raspberry Pi Platform and Python Programming for the Raspberry Pi

The Raspberry Pi Platform and Python Programming for the Raspberry Pi

The Raspberry Pi is a small, affordable single-board computer that you will use to design and develop fun and practical IoT devices while learning programming and computer hardware. In addition, you will learn how to set up up the Raspberry Pi environment, get a Linux operating system running, and write and execute some basic Python code on the Raspberry Pi. You will also learn how to use Python-based IDE (integrated development environments) for the Raspberry Pi and how to trace and debug Python code on the device. Please note that this course does not include discussion forums.

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  • 11 hours
  • English
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Introduction to Data Science in Python

Introduction to Data Science in Python

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively.

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  • 35 hours
  • English
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Introduction to Python Programming

Introduction to Python Programming

This course provides an introduction to programming and the Python language. Students are introduced to core programming concepts like data structures, conditionals, loops, variables, and functions. This course includes an overview of the various tools available for writing and running Python, and gets students coding quickly. It also provides hands-on coding exercises using commonly used data structures, writing custom functions, and reading and writing to files.

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  • 28 hours
  • English
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Python Data Visualization

Python Data Visualization

This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data.

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  • 9 hours
  • English
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