Programming with Python for Data Science

Data Science colleagues, this program was developed in partnership with Coding Dojo and targets individuals who have introductory level Python programming experience. The course teaches students how to start looking at data with the lens of a data scientist by applying efficient, well-known mining models in order to unearth useful intelligence, using Python, one of the popular languages for Data Scientists. Topics include data visualization, feature importance and selection, dimensionality reduction, clustering, and classification. All of the data sets used in this course are gathered live-data or inspired by real-world domains that can benefit from machine learning. The course objectives are: What machine learning is and the types of problems it is adept to solving, how to represent raw data in a manner conducive to deriving valuable information, how to use various data visualization techniques, how to use principal component analysis and isomap intelligently to simplify your data, how to apply supervised learning algorithms to your data, and Concepts such as model selection, pipelining, and cross validation. Training modules include: 1) Data and Features, 2) Exploring Data, 3) Transforming Data, 4) Data Modeling, 5) Evaluating Data, and 6) Final Exam and Course Wrap-Up. Much career success, Lawrence Wilson - Artificial Intelligence Academy

Enroll today at: https://tinyurl.com/y3r53dv3     

Analyzing Big Data with Microsoft R Server and Client – Ramp-up your career and income potential

Colleagues, Microsoft R Open is the enhanced distribution of R from Microsoft Corporation. It is a complete open source platform for statistical analysis and data science. The main purpose of the course is to give students the ability to use Microsoft R Server to create and run an analysis on a large dataset, and show how to utilize it in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database. After completing this course, students will be able to: Explain how Microsoft R Server and Microsoft R Client work, Use R Client with R Server to explore big data held in different data stores, Visualize data by using graphs and plots, Transform and clean big data sets, Implement options for splitting analysis jobs into parallel tasks, Build and evaluate regression models generated from big data, Create, score, and deploy partitioning models generated from big data, and Use R in the SQL Server and Hadoop environments. You will gain high demand, marketable skills in: 1) Microsoft R Server and R Client, 2) Exploring Big Data, 3) Visualizing Big Data, 4) Processing Big Data, 5) Parallelizing Analysis Operations, 6) Creating and Evaluating Regression Models, 7) Creating and Evaluating Partitioning Models, and 8) Processing Big Data in SQL Server and Hadoop. Career success awaits you, Lawrence Wilson - Artificial Intelligence Academy

Register today at: https://tinyurl.com/y3e3nfud   

Deep Learning Specialization - Master Deep Learning & Break into Artificial Intelligence (New career & earnings opportunities)

Colleagues, in five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.  You will gain valuable skills in: Tensorflow, Convolutional Neural Network, Artificial Neural Network, and Deep Learning. The five courses in in this Specialization include: Neural Networks and Deep Learning, Improving Deep Learning Networks with Hyperparameter Tuning, Regularization and Optimization, Structuring Deep Learning Projects, Convolution Neural Networks, and Sequence Model. Much career success, Lawrence Wilson - Artificial Intelligence Academy

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

Take your Machine Learning and Cloud career to the next level – Machine Learning Fundamentals with Amazon SageMaker on AWS

Colleagues, this Machine Learning Fundamentals with Amazon SageMaker on AWS LiveLessons training program teaches the fundamental concepts and taxonomy for machine learning. The program provides a high-level overview of the tools, languages, and libraries that Amazon SageMaker uses, including the AWS console, Jupyter Notebooks, languages such as Python, and interactive data analysis libraries such as Pandas. This course will also discuss common algorithms and models used with ML and Amazon SageMaker, which will help determine the appropriate model to use in specific business scenarios. Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly. Amazon SageMaker is a fully-managed service that covers the entire machine learning workflow to label and prepare your data, choose an algorithm, train the model, tune and optimize it for deployment, make predictions, and take action. This program is comprised of five training modules: 1) Amazon SageMaker, 2) Fundamentals Machine Learning Concepts with Practical Applications, 3) Amazon SageMaker Supporting Tools and Technologies, 4) Data and Model Management with Amazon SageMaker, and 5) Predictions and Deployment with Amazon SageMaker. Much career success, Lawrence Wilson – Artificial Intelligence Academy

Enroll today at: https://tinyurl.com/y25f8sgr    

Microsoft Cloud Data Science with Azure Machine Learning Certification – Take your career & income to the next level

AI and Cloud Pros, did you know that the average salary for a Machine Learning expert with Microsoft Azure skills is $128k per year. Explore and use R and R Server with Azure Machine Learning, and explain how to deploy & configure SQL Server to support R services. This training program teaches you how to use Azure HDInsight for big data processing, data mining, real-time analytics, and predictive modeling. The main purpose of the course is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use of machine learning with big data tools such as HDInsight and R Services. This course also prepares the students for the Microsoft 70-774: Perform Cloud Data Science with Azure Machine Learning certification exam. You will be equipped for Azure Machine Learning, Managing Datasets, Preparing Data for use with Azure Machine Learning, Using Feature Engineering and Selection, Building Azure Machine Learning Models, Classification and Clustering with Azure machine learning models, Using R and Python with Azure Machine Learning, Initializing and Optimizing Machine Learning Models, Using Azure Machine Learning Models, Cognitive Services, HDInsight, and R Services. Much career success, Lawrence Wilson – Artificial Intelligence Academy

Register today at: https://tinyurl.com/y56g5gj2

Machine Learning and AI with Python and Jupyter Notebook Training - Accelerate your earnings & career potential

Artificial Intelligence colleagues, this valuable training program includes over eighth hours of Video Instruction. Learn just the essentials of Python-based Machine Learning on AWS and Google Cloud Platform with Jupyter Notebook. This LiveLesson video course shows how AWS and Google Cloud Platform can be used to solve real-world business problems in Machine Learning and AI. This program will equip you to: Understand Data Science concepts and Python fundamentals for Machine Learning, how to develop a Data Engineering API with Flask and Pandas, walk through of EDA (exploratory data analysis), Explain Python and AWS, Python programming and the Google Cloud Platform. Much career success, Lawrence Wilson – Artificial Intelligence Academy

Register today at: https://tinyurl.com/yxq5pf2s

Attention Machine Learning & Cloud Professionals: Data Engineering, Big Data, and Machine Learning on GCP Specialization – Time to jumpstart your career income growth

Software Developers, this Specialization program represents the nexus of Machine Learning and Cloud Computing – two of the fastest growing segments of the global IT sector. The program teaches the following skills: Design and build data processing systems on Google Cloud Platform, Leverage unstructured data using Spark and ML APIs on Cloud Dataproc, Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow, derive business insights from extremely large datasets using Google BigQuery, Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML, and Enable instant insights from streaming data. The five courses which comprise this Specialization are: 1) Google Cloud Platform Big Data and Machine Learning Fundamentals, 2) Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform, 3) Serverless Data Analysis with Google BigQuery and Cloud Dataflow, 4) Serverless Machine Learning with Tensorflow on Google Cloud Platform, and 5) Building Resilient Streaming Systems on Google Cloud Platform. Career success awaits you, Lawrence Wilson - Artificial Intelligence Academy.

Enroll today at: https://fxo.co/6Hnx

Join over 2.5m+ professionals who have enrolled in the Machine Learning program from Stanford University

Software Developers and Engineers, this program provides a broad introduction to machine learning, data mining, 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). The course will also draw from numerous case studies and applications, so that you will also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas. You will gain valuable skills in: Logistic Regression, Artificial Neural Network, Machine Learning (ML),  Algorithms, Machine Learning. Training Modules include: Linear Regression with One Variable, Linear Algebra Review, Linear Regression with Multiple Variables, Octave/Matlab Tutorial, Logistic Regression, Regularization, Neural Networks: Representation, Neural Networks: Learning, Advice for Applying Machine Learning, Machine Learning System Design, Support Vector Machines, Unsupervised Learning, Dimensionality Reduction, Anomaly Detection, Recommender Systems, Large Scale Machine Learning, Application Example: Photo OCR … plus multiple Electives. Much career success, Lawrence Wilson – Artificial Intelligence Academy

Enroll now at: https://fxo.co/87TG