Machine Learning with TensorFlow on Google Cloud Platform

ML & Cloud colleagues, join over 75k professionals enrolled in Machine Learning with TensorFlow on Google Cloud Platform. Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem. Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems. You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform.Gain high-demand skills in Tensorflow, Machine Learning, Feature Engineering, Cloud Computing, APIs,, Inclusive ML, Google Cloud Platform, Bigquery, Data Cleansing, Python Programming and Data Pipelines. Training modules include: 1)  How Google does Machine Learning, 2)  Launching into Machine Learning, 3) Introduction to TensorFlow, 4) Feature Engineering, and 5) Art and Science of Machine Learning

Enroll today (individuals & teams): https://tinyurl.com/y4kvqe9g 

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

Data Science: Data-Driven Decision Making

Colleagues, discover storytelling with data and make better business decisions using data wrangling, modelling, and visualisations in R in this Data Science: Data-Driven Decision Making program. Gain high-demand skills in Data wrangling, R programming, Developing data analysis workflows, Work with and visualise spatial and temporal data, Developing statistical models, Harvesting data, Tidying data, Data collection methods, Data visualisation and Data analysis. The three skill-based training modules include: 1) Wrangling and Workflow: Get an introduction to data science and learn how to make the most of your data through effective data wrangling and storytelling (4 weeks - 12 hours per week), 2) Modelling and Visualisation: Explore the role of data visualisation in data science, and learn how to use and apply data modelling techniques (4 weeks - 12 hours per week), and 3) Formats, Ethics, and Storytelling: Evaluate the challenges of data variety, ethics, and privacy on this course in Monash University's data science microcredential (4 weeks - 12 hours per week).

Enroll today (individuals & teams): https://fxo.co/AMzY 

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

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) 

Artificial Intelligence on Microsoft Azure: Machine Learning and Python Basics (AZ-900 & AI-100 Certification Exam Prep)

AI and Cloud  colleagues, this comprehensive program will equip you to pass the  voucher to sit the Microsoft Azure Fundamentals (AZ-900) and Microsoft Azure AI Engineer Associate (AI-100) certification exams (receive exam vouchers upon completion of this program). Develop AI and machine learning skills using Python and Microsoft Azure, on the path to role-based certifications. Skill-based training modules - mapped to the cert exams, include: 1) Microsoft Future Ready: Azure Cloud Fundamentals, 2) Microsoft Future Ready: Introduction to Artificial Intelligence, 3) Microsoft Future Ready: Introduction to Python Programming, 4) Microsoft Future Ready: Essential Mathematics for Machine Learning and AI, and 5) Microsoft Future Ready: Designing and Implementing an Azure AI Solution (AI Engineer Associate). 

Enroll today at: https://fxo.co/9mGh 

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

Intel® Edge AI for IoT Developers (Nanodegree Program)

Dev colleagues, this nanodegree program leverages the Intel® Distribution of OpenVINO™ Toolkit to fast-track development of high-performance computer vision and deep learning inference applications, and run pre-trained deep learning models for computer vision on-premise. You will identify key hardware specifications of CPU, VPU, FPGA, and Integrated GPU hardware types and utilize the Intel® DevCloud for the Edge to test model performance on the various hardware types. Use software tools to optimize deep learning models to improve performance of Edge AI systems. The three skill-based training modules(each with a hands-on project) include: 1) Edge AI Fundamentals with OpenVINO™ (Project: Deploy a People Counter at the Edge), 2) Hardware for Computer Vision & Deep Learning Application Deployment .(Project: Design a Smart Queuing System)., and 3) Optimization Techniques and Tools for Computer Vision & Deep Learning Applications (Project:Build a Computer Pointer Controller).  This program requires intermediate knowledge of Python, and experience with Deep Learning, Command Line, and OpenCV.

Enroll today at: https://fxo.co/9kvZ 

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

Natural Language Processing Engineer with Python Certification

Software colleagues, this Natural Language Processing Engineer with Python program will take you through the essentials of text processing all the way up to classifying texts using Machine Learning algorithms. You will learn various concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing and so on using Python’s most famous NLTK package. Once you delve into NLP, you will learn to build your own text classifier using the Naïve Bayes algorithm. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language.  You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. You will gain high demand, marketable skills in: 1) Introduction to Text Mining and NLP, 2) Extracting, Cleaning and Pre-processing and Machine Learning, 3) Analyzing Sentence Structure, 3) Text Classification – I & II, and 4) In Class Project on Sentiment Classification.

Register today at: https://fxo.co/8m2j 

Career success awaits you, Lawrence Wilson – Artificial Intelligence Academy (AIA)

Machine Learning Engineer Training ($130k+ average salary)

ML colleagues, according to ZipRecruiter Machine Learning Engineers earn $130,530 per year. Learn advanced machine learning techniques and algorithms -- including how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application, evaluate the performance of your models, A/B test models and update the models as you gather more data..Suggested prerequisites are intermediate knowledge of Python and Machine Learning algorithms. The four skill-based training modules (each with a unique training project) include: 1) Software  Engineering Fundamentals (Project: Build a Python Package), 2) Machine  Learning in Production with Amazon SageMaker (Project: Deploy a Sentiment Analysis Model), 3) Machine Learning Case Studies (Project: Plagiarism Detector), and 4) Machine Learning Capstone (Project: Select a machine learning challenge and propose a possible solution). 

Enroll today at: https://fxo.co/9glo 

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

Machine Learning Program with Andrew Ng (Stanford University)

ML colleagues, join over 3.5m students enrolled in this foundational program on machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). Also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio and database mining, Training modules include: 1) Linear Regression (single variable) and Algebra, 2) Linear Regression (multivariate) and Octave/Matlab Tutorial, 3) Logistic Regression and Regularization, 4) Neural Networks: Representation, 5) Neural Networks: Learning, 6) Advice for Applying Machine Learning and Machine Learning System Design, 7) Support Vector Machines, 8) Unsupervised Learning and Dimensionality Reduction, 9) Anomaly Detection and Recommender Systems, 10) Large Scale Machine Learning and 11) Application Example: Photo OCR.

Enroll today at: https://tinyurl.com/yxagguo8 

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

Data Science with Python Specialization (University of Michigan)

Data Science colleagues, join over 217,000 professionals who have achieved their Applied Data Science with Python Specialization. This skills-based specialization is intended for learners who have a basic Python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through Python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Gain high-demand skills in Text Mining, Python Programming, Pandas, Matplotlib, Numpy Data Cleansing, Data Virtualization and  Visualization (DataViz), Machine Learning (ML), Algorithms, Machine Learning, Scikit-Learn, and Natural Language Toolkit (NLTK). The five courses which comprise this Specialization include: 1) Data Science in Python, 2) Plotting, Charting and  Data Representation in Python, 3) Machine Learning in Python, 4) Text Mining in Python, and 5)  Social Network Analysis in Python. 

Enroll today at: https://tinyurl.com/y2k3pq6u 

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

AI and Deep Learning with TensorFlow

AI and Deep Learning in TensorFlow with Python Certification Training master the concepts of SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. Gain high-demand skills in Deep Learning and TensorFlow Concepts, Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Keras, TFlearn, Autoencoders, Restricted Boltz-mann Machine (RBM), Neural Networks & Natural Language Processing (NLP), Python with TensorFlow Libraries, Text Analytics and Processing.  Training modules include: 1) Introduction to Deep Learning, 2) Neural Networks with TensorFlow, 3) Deep Networks, 4) Convolutional Neural Networks (CNN), 5 )Recurrent Neural Networks (RNN), 6) Restricted Boltzmann Machine (RBM) and Autoencoders, 7) Keras API, 8) TFLearn API, and 9) In-Class Project.

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

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

Python Spark Certification Training using PySpark (CCA175)

Big Data Architects, Engineers and Developers - PySpark Certification Training will equip you to become a successful Spark Developer using Python and pass the Cloudera Hadoop and Spark Developer Certification Exam (CCA175). Gain in-depth knowledge of Apache Spark and the Spark Ecosystem including Spark RDD, Spark SQL, Spark MLlib and Spark Streaming and acquire comprehensive knowledge of Python Programming language, HDFS, Sqoop, Flume, Spark GraphX and Messaging System such as Kafka. Skill-based training modules cover: 1) Big Data Hadoop and Spark, 2) Python for Apache Spark, 3) Functions, OOPs, and Modules in Python, 4) Apache Spark Framework, 5) Spark RDDs, 6) DataFrames and Spark SQL, 7) Machine Learning using Spark MLlib, 8) Spark MLlib - Deep Dive, 9) Apache Kafka and Apache Flume, 10) Apache Spark Streaming - Processing Multiple Batches and Data Sources, 11) Implementing an End-to-End Project, and 12) Spark GraphX.

Enroll today at: https://fxo.co/9YCB

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

Deep Learning Specialization

Colleagues, join over 454k+ students worldwide who have learned the foundations of Deep Learning, build neural networks, and lead successful machine learning projects. This program will equip you in Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization and beyond. You will work on case studies from health care, autonomous driving, sign language reading, music generation and natural language processing (NLP). Master theory and see how it is applied in industry using Python and in TensorFlow. Build core skills in TensorFlow, Convolutional Neural Network, Artificial Neural Network, Deep Learning, Back propagation, Python Programming, Hyperparameter Optimization, Machine Learning, Inductive Transfer, Multi-Task Learning and Facial Recognition Systems. Training modules address: 1) Neural Networks and Deep Learning, 2) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, 3) Structuring Machine Learning Projects, 4) Convolutional Neural Networks, and 5) Sequence Models.

Get started today: https://tinyurl.com/y2us98q9

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

Advanced Deployment Scenarios with TensorFlow

ML colleagues, earn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy.  Gain advanced skills in: TensorFlow Serving, Machine Learning, Federated Learning, TensorFlow Hub, TensorBoard. Training modules cover: 1) TensorFlow Extended, 2) Pre-trained models with TensorFlow Hub, 3) TensorBoard: Tools for Model Training and 4) Federated Learning.

Enroll today at: https://tinyurl.com/yyuua8lc

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

Amazon Machine Learning (Training)

ML colleagues, this Amazon Machine Learning includes over 20 independent lessons totaling more than 3 hours of instruction with demos, interactive hands-on labs and detailed slide explanations. You will be equipped to solve for personalization, search, marketing, finance, productivity, and management efficiency using AML, configure a schema, and set up a data source using “small data” in S3, use data insights and visualization tools, leverage Features, Targets, Observations, Labeled Data, Unlabeled Data, and Ground Truth to prepare historical data for predictive analysis, and prepare data for use in a regression model and a multi-class model. Skill-based training modules address: 1) Machine Learning Basics, 2) Machine Learning Data Architecture, 3) Data and Schema Configuration, 4) Visualization and Modeling, and 5) Predictions with Amazon Machine Learning. Hands-on labs Usage scenarios are provided to inspire viewers to create their own value-added services on top of Amazon Machine Learning.

Enroll today at: https://tinyurl.com/y3krtokl

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

Python for Data Science Certification

Data Science colleagues, this Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines. Gain skills that will strengthen your career and equip you to pass the certification exam, including: 1) Sequences and File Operations, 2) Deep Dive – Functions, OOPs, Modules, Errors and Exceptions, 3) NumPy, Pandas and Matplotlib, 4) Data Manipulation, 5) Machine Learning with Python, 6) Supervised Learning, 7) Dimensionality Reduction, 8) Unsupervised Learning, 9) Association Rules Mining and Recommendation Systems, 10) Reinforcement Learning, 11) Time Series Analysis, plus 12) Model Selection and Boosting.

Register today at: https://fxo.co/9QE9

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

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Colleagues, join over 170k professionals who have enrolled in this new deeplearning.ai TensorFlow Specialization. Andrew Ng teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. Gain valuable core skills in Computer Vision, TensorFlow and Machine Learning. Training modules address: 1) A New Programming Paradigm, 2) Introduction to Computer Vision, 3) Enhancing Vision with Convolutional Neural Networks, and 4) Using Real-world Images. Learn best practices for using TensorFlow, build a basic neural network in TensorFlow, understand how to use convolutions to improve your neural network, and train a neural network for a computer vision application.

Begin your journey today. Enroll at: https://tinyurl.com/yy7q4f4n

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

AI & Deep Learning in TensorFlow with Python (Deep Learning Engineer Certification)

Artificial Intelligence colleagues, join 1000s of professional at companies like VMware, Cisco, Dell and Honeywell who earned their Deep Learning Engineer Certification. You will learn about AI, neural networks, deep learning frameworks, and implementing machine learning algorithms using Deep Networks. We will also explore how different layers in neural networks does data abstraction and feature extraction using Deep Learning. Deep Learning in TensorFlow training is designed to make you a Data Scientist by providing you rich hands-on training on Deep Learning in TensorFlow with Python. This course is a stepping stone in your Data Science journey using which you will get the opportunity to work on various Deep Learning projects. Skill-based training modules include: 1) Introduction to Deep Learning, 2) Understanding Neural Networks with TensorFlow, 3) Deep dive into Neural Networks with TensorFlow, 4) Master Deep Networks, 4) Convolutional Neural Networks (CNN), 5) Recurrent Neural Networks (RNN), 6) Restricted Boltzmann Machine (RBM) and Autoencoders, 6) Keras API, and 7) TFLearn API ... along with an in-class Capstone Project.

Enroll today at: https://fxo.co/9PYj

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

AWS Certified Machine Learning-Specialty Training (ML-S)

ML colleagues, this program includes 7 hours of training that will equip you to pass the AWS Machine Learning-Specialty (ML-S) Certification exam. Data Engineering instruction covers the ingestion, cleaning, and maintenance of data on AWS. Exploratory Data Analysis (EDA) covers topics including data visualization, descriptive statistics, and dimension reduction and includes information on relevant AWS services. Machine Learning Modeling addresses feature engineering, performance metrics, overfitting, and algorithm selection. Operations covers deploying models, A/B testing, using AI services versus training your own model, and proper cost utilization. Skill-based modules focus on: 1) AWS Machine Learning-Specialty (ML-S) Certification, 2) Data Engineering for ML on AWS, 3) Exploratory Data Analysis on AWS, 4) Machine Learning Modeling on AWS, 5) Operationalize Machine Learning on AWS, 6) Create a Production Machine Learning Application, and 7) Case Studies on Sagemaker, DeepLense, Kinesis Features, AWS Flavored Python and Cloud9.

Register today at: https://tinyurl.com/ya6ko8sg

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

Building Artificial Intelligence Apps on Google Cloud Platform

AI and GCP colleagues, this innovative training program is designed for developers who want to expand their Data Science skills and build AutoML applications in the Cloud. You will learn how to use AutoML, Big Query, Python, and Google App Engine to create sophisticated AI applications. Cloud AutoML is a suite of machine learning products that allows developers with limited machine learning expertise to train high-quality models specific to their business needs. It relies on Google’s state-of-the-art transfer learning and neural architecture search technology. Developers use Cloud AutoML’s graphical user interface to train, evaluate, improve, and deploy models based on their data. The seven (7) training modules will equip you to: 1) Create an Application Skeleton on GCP using Google App Engine, 2) Build ETL (Extract Transform Load) Pipelines, 3) Use ML Prediction on BigQuery, 4) Use AutoML, 5) Use AI Platform, 6) Build an Analytics Application, and 7) Implement Build Systems and Containers.

Enroll today at: https://tinyurl.com/y8zwv3lf

Much career success, Lawrence E. Wilson - Online Learning Central (OLC) and Artificial Intelligence Academy (AIA)

Data Science Specialization Training – Johns Hopkins University

Colleagues, this Data Science Specialization from one of America’s top universities will equip you to use R to clean, analyze, and visualize data, Use GitHub to manage data science projects, Navigate the entire data science pipeline from data acquisition to publication, and Perform regression analysis, least squares and inference using regression models. This Specialization includes ten courses: Data Scientist’s Toolbox, R Programming, Cleaning Data, Exploratory Data Analysis, Reproducible Data, Statistical Inference, Regression Models, Practical Machine Learning, Developing Data Products and a Data Science Capstone Project.

Register today at: https://fxo.co/7ux5

Much career success, Lawrence Wilson –  Artificial Intelligence Academy