Machine Learning Engineer for Microsoft Azure ($147k salary)

ML & Cloud colleagues, strengthen your machine learning skills and build practical experience by training, validating, and evaluating models with this Machine Learning Engineer for Microsoft Azure nanodegree program. According to Indeed the average MLE for MS Azure earns over $146k USD per year. The training modules - each with their own project - are the core of this program: 1)  Using Azure Machine Learning: Learn how to configure machine learning pipelines in Azure, identify use cases for Automated Machine Learning, and use the Azure ML SDK to design, create, and manage machine learning pipelines in Azure (Project: Optimizing an ML Pipeline in Azure), 2) Machine Learning Operations: Operationalizing machine learning, from selecting the appropriate targets for deploying models, to enabling Application Insights, identifying problems in logs, and harnessing the power of Azure’s Pipelines (Project: Operationalizing Machine Learning). and 3) Capstone Project: The program capstone gives you the opportunity to use the knowledge you have obtained from this Nanodegree program to solve an interesting problem. You will have to use Azure’s Automated ML and HyperDrive to solve a task (Project: Training and Deploying an ML Model in Azure). This program comes with an Experienced Project Reviewers, Technical Mentor Support and Personal Career Coach.

Register today (individuals & teams): https://fxo.co/AGNS 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Unsupervised Learning: Clustering

AI, ML colleagues, this  program will focus on Unsupervised Learning Clustering algorithms and methods for Machine Learning through practical examples and code. The course has code and sample data for you to run and learn from. It also encourages you to explore your own datasets using Clustering algorithms. Students who are interested in a practical introduction to clustering, a kind of unsupervised machine learning. Want an intuitive understanding of the theory behind clustering. Students can use these methods and algorithms for hot applications such as marketing analytics, customer segmentation, anomaly detection, fraud detection, and other practical applications in their respective fields. Skill-based training modules address: 1) K-Means Clustering, 2) Gaussian Mixture Models (GMMs), 3) Hierarchical Clustering, 4) Methods for Selecting Number of Clusters, 5) Evaluating the Quality of the Clustering, 6) Industry Applications, 7) Mini-Project: Pulling It All Together, and 9) Mini-Project Solution Preview, and 10) Solution Preview.

Enroll today (individuals & teams):https://tinyurl.com/rm6rx5v  

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Deep Learning with TensorFlow 2.0 (Certification & Training)

ML/DL colleagues, this Deep Learning with TensorFlow 2.0 Certification Training is curated by experienced industry professionals. This course will help you master popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python. You will work on real-time projects like Emotion and Gender Detection, Auto Image Captioning using CNN and LSTM, and many more. Skill-based training modules address: 1) Introduction to Deep Learning, 2) Getting Started with TensorFlow 2.0, 3) Convolution Neural Networks, 4) Regional CNN, 5) Boltzmann Machine & Autoencoder, 6) Generative Adversarial Networks (GANs), 7) Emotion and Gender Detection, 8) Introduction RNN and GRU, 9) Long Short-term Memory (LSTM), and 10) Auto Image Captioning Using CNN LSTM.

Enroll today (individuals & teams): https://tinyurl.com/y6d2t8hd  

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

TensorFlow 2 for Deep Learning Specialization

DL Colleagues, the TensorFlow 2 for Deep Learning Specialization is intended for machine learning researchers and practitioners who need practical skills in the popular deep learning framework TensorFlow. Gain hands-on skills in Tensorflow, TensorFlow Probability, Probabilistic Neural Networks, Keras, Deep Learning Probabilistic Neural Network, Generative Models and Probabilistic Programming Language (PRPL). Three core training modules will equip you in: 1 - Getting started with TensorFlow 2 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, and implementing callbacks, 2 - Customising your models with TensorFlow 2 you will deepen your knowledge and skills with TensorFlow - develop fully customised deep learning models and workflows for any application using lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow, and 3 - Probabilistic Deep Learning with TensorFlow 2  focuses on the probabilistic approach to deep learning. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real world datasets. 

Register today at: https://tinyurl.com/y3zy56j4  

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Advanced Machine Learning Specialization

ML colleagues, this Advanced Machine Learning Specialization provides an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems. Gain high-demand skills in Recurrent Neural Network, Tensorflow, Convolutional Neural Network, Deep Learning, Data Analysis, Feature Extraction, Feature Engineering, Xgboost, Bayesian Optimization, Gaussian Process, Markov Chain Monte Carlo (MCMC) and Variational Bayesian Methods. Skill-based training modules address: 1) Introduction to Deep Learning, 2) How to Win a Data Science Competition: Learn from Top Kagglers, 3) Bayesian Methods for Machine Learning, 4) Practical Reinforcement Learning, 5) Deep Learning in Computer Vision, 6) Natural Language Processing, and 7) Addressing Large Hadron Collider Challenges by Machine Learning.

Enroll today at: https://tinyurl.com/yy7bbh9w 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

IBM Applied AI Professional Certificate

AI colleagues, the IBM Applied AI Professional Certificate program will give you a firm understanding of AI technology, its applications, and its use cases. You will become familiar with concepts and tools like machine learning, data science, natural language processing, image classification, image processing, IBM Watson AI services, OpenCV, and APIs. Learn to use IBM Watson AI services and APIs to create smart applications with minimal coding. By the end of this Professional Certificate. The six skill-based training modules address: 1 - Introduction to Artificial Intelligence (AI), 2 - Getting Started with AI using IBM Watson, 3 - Building AI Powered Chatbots Without Programming, 4 - Python for Data Science and AI, 5 - Building AI Applications with Watson APIs, and 6 - Introduction to Computer Vision with Watson and OpenCV.

Enroll today at: https://tinyurl.com/y6qjakgn 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Python Data Analysis with NumPy and Pandas (Training)

Dev colleagues, this advanced programming course will teach you how to analyze Python data with NumPy and pandas. As machine learning becomes more prevalent, Python has emerged as a scientific language. Within Python, NumPy and pandas are essential for any scientific computation. Understanding how these elements work together is critical for the aspiring data scientist - work with Jupyter Notebook, use NumPy to work with arrays and matrices of numbers, work with Pandas to analyze data and with Matplotlib from within Pandas. Three core training modules include: 1) Jupyter Notebooks, 2) NumPy, and 3) Pandas. The program consists of 28 individual courses that can be taken over a 3 month period - open enrollment.

Register today at: https://tinyurl.com/yymfr7rl 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Advanced Artificial Intelligence on Microsoft Azure: Deep Learning, Reinforcement Learning and Applied AI

AI & ML colleagues, build advanced AI programming skills using Microsoft Azure and upskill for roles in AI, analytics, data science, and deep learning. Six skill-based training modules comprise this program, including: 1) Microsoft Future Ready: Designing and Implementing an Azure AI Solution (AI Engineer Associate), 2)  Microsoft Future Ready: Reinforcement Learning Fundamentals, 3) Applied Artificial Intelligence: Speech Recognition Systems, 4) Applied Artificial Intelligence: Natural Language Processing (NLP), 5) Microsoft Future Ready: Deep Learning Fundamentals, and 6) Applied Artificial Intelligence: Computer Vision and Image Analysis. Upon successful completion of this Professional Certificate, you receive a voucher to sit the Azure AI Engineer Associate (AI-100) certification exam. Voucher. You also receive Digital Completion Certificates and hands-on lab accomplished digital badges.

Enroll today at: https://fxo.co/AA6a 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Deep Learning with TensorFlow 2.0 Certification Training

Machine Learning colleagues, become certified as a Deep Learning Engineer. This Deep Learning with TensorFlow 2.0 Certification Training is curated with the help of experienced industry professionals per the latest requirements & demands. You will master popular algorithms like CNN, RCNN, RNN, LSTM, RBM using TensorFlow 2.0 in Python. Work on real-time projects like Emotion and Gender Detection, Auto Image Captioning using CNN, LSTM, and many more. Skill-based training modules address: 1) Introduction to Deep Learning, 2) Getting Started with TensorFlow 2, 3) Convolutional Neural Network, 4) Regional CNN, 5) Boltzmann Machine & Autoencoder, 6) Generative Adversarial Network(GAN), 7) Emotion and Gender Detection, 8) Introduction RNN and GRU, 9 ) LSTM,  and 10) Auto Image Captioning Using CNN LSTM.

Register today. Visit: https://fxo.co/9PYj 

Much career success, Lawrence E. Wilson -  Artificial Intelligence Academy (AIA) 

Data Scientist with Python (Nanodegree Program)

Software & Analytics colleagues, master the skills necessary to become a successful Data Scientist. You will work on projects designed by industry experts, run data pipelines, design experiments, build recommendation systems, and deploy solutions to the cloud. Skill-based training modules and hands-one projects include: 1) Solving Data Science Problems (Project: Write a Data Science blog post), 2) Software Engineering for Data Scientists, 3) Data Engineering for Data Scientists (Project: Build a data science pipelines with Figure Eight), 4) Experiment Design and Recommendations (Project: Design a recommendation engine with IBM), and 5) Data Science Projects (Project: Data science capstone project). Recommended prerequisites: familiarity with machine learning concepts, Python programming, probability, and statistics. 

Register today: https://fxo.co/9nmz  

Much career success, Lawrence E. Wilson -  Artificial Intelligence Academy (AIA)