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)