Applied Machine Learning Algorithms with Python – Take the next step in your AI career & income path

Software and Data Science colleagues, the Corporate Finance Institute (CFI) has partnered with Machine Learning Edge to bring to you a unique course on the applied machine learning algorithms for finance professionals. This course will utilize the knowledge you learned from the Python Fundamentals course to build machine learning investor classifiers. We are going to explore real case studies from investment banking and capital markets applications that are being used today to advise Fortune 500 companies all over the world. By the end of the course you will be able to: Identify overfit regression models, Compare different regularized regression algorithms and decision tree ensemble algorithms Explain the confusion matrix and its relation to the ROC curve, Construct training data sets, testing data sets, and model pipelines, perform advanced data cleaning, exploration, and visualization, Engineer features based on conditional relationships between existing features, and Build and finalize a machine learning classifier. Core skills you will acquire are: 1) Data Cleaning and Exploration, 2) Data Visualization with Matplotlib and Seaborn,Seaborn Countplot Function, 4) Replace Function and Sparse Classes, 5) Null Values, 6) Drop Null Values, 7) Boxplots with Seaborn, 8) Saving Cleaned Data Table, 9) Regression Algorithms, 10) Liquidity Regressor, and 12) Classification Algorithms Investor Classifiers I & II. Much career success, Lawrence Wilson – Online Learning Central

Register today at: https://tinyurl.com/r2jegmz

Microsoft Professional Program - Data Science Orientation: Launch you Data Science career & income path

Attention all Data Scientists and Analysts, this program is the first stop in the Data Science curriculum from Microsoft. It will help you get started with the program, plan your learning schedule, and connect with fellow students and teaching assistants. Along the way, you’ll get an introduction to working with and exploring data using a variety of visualization, analytical, and statistical techniques. Course Objectives: How the Microsoft Data Science curriculum works, how to navigate the curriculum and plan your course schedule, Basic data exploration and visualization techniques in Microsoft Excel, and Foundational statistics that can be used to analyze data. The program includes:  1) The Data Science Curriculum - Guide to the Data Science Curriculum and Meet the Data Scientists, 2) Data Science Fundamentals - Getting Started with Data, and 3) A Basic Introduction to Statistics, and 4) Lab exploring Data with Excel. Much career success, Lawrence Wilson – Artificial Intelligence Academy   

Why not enroll today? Visit: https://tinyurl.com/ssnl4gu

Data Science Specialization from John’s Hopkins University – Advance your professional & income potential

Data Scientists and Software Engineers, launch Your Career in Data Science with this introduction to data science, developed and taught by leading professors. Learning Objectives include: Use R to clean, analyze, and visualize data, Navigate the entire data science pipeline from data acquisition to publication, Use GitHub to manage data science projects, perform regression analysis, least squares and inference using regression models. Gain high demand, marketable skills in GitHub, Machine Learning, R Programming and Regression Analysis. The training modules which comprise this program are: 1) R Programming, 2) Getting and Cleaning Data, 3) Exploratory Data Analysis, 4) Reproducible Research, 5) Statistical Inference, 6) Regression Models, 7) Practical Machine Learning, 8) Developing Data Products, and 9) Data Science Capstone. Much career success, Lawrence Wilson – Artificial Intelligence Academy   

Why not enroll today? Visit:  https://fxo.co/8MKj

Model Tuning for Machine Learning – Advance your Artificial Intelligence career & income horizons

Machine Learning Pros, this course will help your slingshot the predictive capabilities of your models, far out-pacing the limits of out-of-box ML. From a ground-up perspective, we'll understand how a model functions, the part of the model that is able to fit the data on its' own, and how important additional tuning and fitting by a trained ML engineer is. This module includes real-world examples, coding assignments, and lots of in-depth exploration of how and why model tuning should be done. If you understand the material in this course, your models will improve, and the results you will be able to deliver will as well! Exceed the performance of out-of-box machine learning models - drastically! You will learn how to make sure you are getting the best predictions your model can provide, if you should change your model, or even if you could benefit from packaging multiple models together to get the best fit for your data. This program is a crucial step towards becoming an expert data scientist - moving from simply knowing how machine learning works, to understanding on an intuitive level how these algorithms model data, and the state of the art techniques that are available to improve their performance. Core skill-based training modules include:  1) Model Tuning Introduction, 2) Bagging, 3) Boosting, 4) Hyper-Parameters, and 5) Stacking. Much career success, Lawrence Wilson – Artificial Intelligence Academy   

Why not enroll today? Visit: https://tinyurl.com/r8krgqq    

Python Django Certification Training – Time to jumpstart your Python career & income opportunities

Software Developers and Engineers, this Django course helps you gain expertise in Django REST framework, Django Models, Django AJAX, Django jQuery etc. You'll master Django web framework while working on real-time use cases and receive Django certification at the end of the course. The Python Django Training and Certification course is intended to help the learner obtain proficiency in Python programming and develop real-world web applications using Django. This course will cover both the basics and the advanced concepts like writing Python scripts, file operations in Python, working with Databases, creating Views, Templates, Forms, Models and REST APIs in Django. Django is a high level Python Web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. It's free and open source. Learning objectives encompass: Know why Python is popular, Setup Python environment, discuss flow control, and Write your first Python program. Training segments include: 1) Learn about Interpreted Languages, 2) List the Advantages/Disadvantages of Python, 3) Explore Pydoc, 4) Start Python, 4) Discuss Interpreter PATH, 5) Use the Interpreter, 6) Run a Python Script, 6) Use Python Scripts on UNIX/Windows, 7) Explore Python Editors and IDEs. Much career success, Lawrence Wilson – Artificial Intelligence Academy   

Why not enroll today? Visit: https://fxo.co/8MLE

Recurrent and Recursive Neural Network Training – Ride the AI-ML tsunami to new income & career growth

Software Developers & Engineers, this program is designed to offer the audience an introduction to recurrent neural network, why and when use recurrent neural network, what are the variants of recurrent neural network, use cases, long-short term memory, deep recurrent neural network, recursive neural network, echo state network, implementation of sentiment analysis using (Recurrent Neural Network) RNN, and implementation of time series analysis using RNN. You will gain a rich understanding of: Understand: What is a recurrent neural network, Different types of networks such as recursive, echo state networks, LSTM (Long Short-term Memory) and deep recurrent network, effectively choose the right recurrent neural network model to solve real-world problems, and Implement a simple recurrent neural network in Python. Core training modules which will expand your marketable skills include: 1) Recurrent Neural Network, 2) Long-short term memory, 3) Deep recurrent neural network, 4) Recursive neural network, 5) Echo state networks, 6) Final exam, and 7) Implement Recurrent neural network step by step in Python. Much career success, Lawrence Wilson – Artificial Intelligence Academy    

Why not enroll today? Visit: https://tinyurl.com/sxnks6d

Unsupervised Learning – Clustering: Punch your ticket to AI-ML career and earnings success

AI & ML Professionals, this training program will focus on Clustering algorithms and methods through practical examples and code. More importantly, it will get you up and running quickly with a clear conceptual understanding. 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. Prerequisites: Beginner knowledge of Python. It's used mostly for expository reasons. You do not need to be a Python expert. Training modules include: 1) K-Means Clustering, 2) Gaussian Mixture Models, 3) Hierarchical Clustering, 4) Methods for Selecting Number of Clusters, 5) Evaluating the Quality of the Clustering, 5) Industry Applications, 6) Mini-Project: Pulling It All Together, and 6) Mini-Project Solution Preview. Much career success, Lawrence Wilson – Artificial Intelligence Academy   

Why not enroll today? Visit:  https://tinyurl.com/rm6rx5v