Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Modeling Time Series and Sequential Data
In this course you learn to build, refine, extrapolate, and, in some cases, interpret models designed for a single, sequential series. There are three modeling approaches presented. The traditional, Box-Jenkins approach for modeling time series is covered in the first part of the course. This presentation moves students from models for stationary data, or ARMA, to models for trend and seasonality, ARIMA, and concludes with information about specifying transfer function components in an ARIMAX, or time series regression, model. A Bayesian approach to modeling time series is considered next.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
Object Localization with TensorFlow
Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs. Think of this task as a simpler version of Object Detection.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Recommender Systems Capstone
This capstone project course for the Recommender Systems Specialization brings together everything you've learned about recommender systems algorithms and evaluation into a comprehensive recommender analysis and design project. You will be given a case study to complete where you have to select and justify the design of a recommender system through analysis of recommender goals and algorithm performance. Learners in the honors track will focus on experimental evaluation of the algorithms against medium sized datasets.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Data Manipulation at Scale: Systems and Algorithms
Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية
Logistic Regression with Python and Numpy
Welcome to this project-based course on Logistic with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery, including gradient descent, cost function, and logistic regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
Big-O Time Complexity in Python Code
In the field of data science, the volumes of data can be enormous, hence the term Big Data. It is essential that algorithms operating on these data sets operate as efficiently as possible. One measure used is called Big-…
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Blockchain Security
This course introduces blockchain security, including a description of how the blockchain works at each level of the blockchain ecosystem. The instructor begins with the building blocks that create the structure of blockchain, the cryptography that it uses for security, and the role of hash functions in the blockchain and how they can be attacked.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Approximation Algorithms Part I
Approximation algorithms, Part I How efficiently can you pack objects into a minimum number of boxes? How well can you cluster nodes so as to cheaply separate a network into components around a few centers? These are examples of NP-hard combinatorial optimization problems. It is most likely impossible to solve such problems efficiently, so our aim is to give an approximate solution that can be computed in polynomial time and that at the same time has provable guarantees on its cost relative to the optimum.
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Course by
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Self Paced
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36 ساعات
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الإنجليزية
Computational Thinking for K-12 Educators Capstone
In this capstone project course, you will learn to support your students in successfully completing the Advanced Placement Principles Create Task -- however this task can be useful for any course as a culminating, student-designed final programming project. You will learn to interpret and practice applying to real sample student work the Create Task rubric and have the option to modify it for your own setting.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
Trading Algorithms
This course covers two of the seven trading strategies that work in emerging markets. The seven include strategies based on momentum, momentum crashes, price reversal, persistence of earnings, quality of earnings, underlying business growth, behavioral biases and textual analysis of business reports about the company. In the first part of the course, you will learn how to read an academic paper. What parts to pay attention to and what parts to skim through will be discussed here.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Introduction to Deep Learning
Deep Learning is the go-to technique for many applications, from natural language processing to biomedical. Deep learning can handle many different types of data such as images, texts, voice/sound, graphs and so on. This course will cover the basics of DL including how to build and train multilayer perceptron, convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders (AE) and generative adversarial networks (GANs).
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Course by
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Self Paced
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60 ساعات
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الإنجليزية
Decryption with Python
By the end of this project, you will be able to apply different decryption algorithms and techniques using Python. Moreover, you will apply cryptography concepts through completing several practical exercises to build a solid foundation in decrypting information and data using several renowned industry encryption algorithms.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Machine Learning - Anomaly Detection via PyCaret
In this 2 hour long project-based course you will learn how to perform anomaly detection, its importance in machine learning, set up PyCaret anomaly detection, create, visualize & compare anomaly detection algorithms all this with just a few lines of code.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Problem Solving, Python Programming, and Video Games
This course is an introduction to computer science and programming in Python. Upon successful completion of this course, you will be able to: 1. Take a new computational problem and solve it, using several problem solving techniques including abstraction and problem decomposition. 2. Follow a design creation process that includes: descriptions, test plans, and algorithms. 3.
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Course by
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Self Paced
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80 ساعات
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الإنجليزية
Association Rules Analysis
The "Association Rules and Outliers Analysis" course introduces students to fundamental concepts of unsupervised learning methods, focusing on association rules and outlier detection. Participants will delve into frequent patterns and association rules, gaining insights into Apriori algorithms and constraint-based association rule mining. Additionally, students will explore outlier detection methods, with a deep understanding of contextual outliers.
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Course by
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Self Paced
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23 ساعات
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الإنجليزية
Introduction to Machine Learning with Python
This course will give you an introduction to machine learning with the Python programming language. You will learn about supervised learning, unsupervised learning, deep learning, image processing, and generative adversarial networks. You will implement machine learning models using Python and will learn about the many applications of machine learning used in industry today. You will also learn about and use different machine learning algorithms to create your models. You do not need a programming or computer science background to learn the material in this course.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Create a Superhero Name Generator with TensorFlow
In this guided project, we are going to create a neural network and train it on a small dataset of superhero names to learn to generate similar names. The dataset has over 9000 names of superheroes, supervillains and other fictional characters from a number of different comic books, TV shows and movies. Text generation is a common natural language processing task. We will create a character level language model that will predict the next character for a given input sequence.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Introduction to Embedded Machine Learning
Machine learning (ML) allows us to teach computers to make predictions and decisions based on data and learn from experiences. In recent years, incredible optimizations have been made to machine learning algorithms, software frameworks, and embedded hardware.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Computer Vision with Embedded Machine Learning
Computer vision (CV) is a fascinating field of study that attempts to automate the process of assigning meaning to digital images or videos. In other words, we are helping computers see and understand the world around us!
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Course by
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Self Paced
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31 ساعات
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الإنجليزية
Basic Game Development with Levels using Scratch
By the end of this project, you will create a basic game using additional features with an introductory, web-based coding program called Scratch. Learning to code will allow you to build basic coding or computer science skills and a fundamental understanding in order to grow your programming abilities. Learners will engage in the design process in order to develop an understanding of how to develop algorithms that control programs, use event-driven programming, and debug a program.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Algorithms, Part I
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. All the features of this course are available for free.
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Course by
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Self Paced
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54 ساعات
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الإنجليزية
App Design and Development for iOS
In App Design and Development for iOS, the third course of the iOS App Development with Swift specialization, you will be developing foundational programming skills to support graphical element presentation and data manipulation from basic functions through to advanced processing. You will continue to build your skill set to use and apply core graphics, touch handling and gestures, animations and transitions, alerts and actions as well as advanced algorithms, threading and more.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Delivery Problem
In this online course we’ll implement (in Python) together efficient programs for a problem needed by delivery companies all over the world millions times per day — the travelling salesman problem. The goal in this problem is to visit all the given places as quickly as possible. How to find an optimal solution to this problem quickly? We still don’t have provably efficient algorithms for this difficult computational problem and this is the essence of the P versus NP problem, the most important open question in Computer Science.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Classical Cryptosystems and Core Concepts
Welcome to Introduction to Applied Cryptography. Cryptography is an essential component of cybersecurity. The need to protect sensitive information and ensure the integrity of industrial control processes has placed a premium on cybersecurity skills in today’s information technology market. Demand for cybersecurity jobs is expected to rise 6 million globally by 2019, with a projected shortfall of 1.5 million, according to Symantec, the world’s largest security software vendor. According to Forbes, the cybersecurity market is expected to grow from $75 billion in 2015 to $170 billion by 2020.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Data Analysis and Representation, Selection and Iteration
This course is the second course in the specialization exploring both computational thinking and beginning C programming. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. Most people have a better understanding of what beginning C programming means! This course assumes you have the prerequisite knowledge from the previous course in the specialization. You should make sure you have that knowledge, either by taking that previous course or from personal experience, before tackling this course.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية