Top 10 Python Developer Certification & Training Programs (#8)

Colleagues, according to ZipRecruiter the average salary of a  Full Stack Python Developer is $121,111. Number 8 on our countdown is the Python: Zero to Coder program from InformIT. While most introductory courses focus on the basics of the language, this course goes one step further to explain how Python is used in practice in the fields of data analysis and web development. Learn fundamental programming concepts, such as conditionals, loops, and functions. They are given hands-on, modular problems to solve so they can progress as they go. Finally, students tie it all together and experiment with some real programming in the form of text-based games. The goal of this course is to equip beginners to learn from scratch, navigate the world of software development, and then kick-start their programming journey with introductions to two of the more common uses of Python: data analysis and web development. Skill-based training modules include: Part I “Learn How to Program Today with Python”: 1 - Introduction to Programming and Python, 2 - Python and Programming Basics, 3 - Control Flow with Conditionals, 4 - Lists and Loops,  5 - Advanced Language Topics, 6 - Introduction to Data Analysis in Python, and 7 - Introduction to Web Development in Python. Part II: “Next Level Python”:  1 - Look at Python Basics, 2 - Work with Files, 3 - Manage Your Python Environments, 4 - Choose an IDE, 5 - Understand Python Modules and Namespaces, 6 - Debug and Test Your Code, 7 - Getting Data from the Web, 8 - Create a Web Scraping Application, and 9 - Put your Project on the Internet.

Enroll today (teams & execs welcome): https://tinyurl.com/4c9xns4m 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe)

Download your complimentary Python, TensorFlow & PyTorch - Career Transformation Guide.

Graphic source: Behance

Top 10 Python Developer Certification & Training Programs (#9)

Colleagues, CareerFoundry estimates average salary for Python Developers in the US at $110,906. We believe this figure will steadily increase as the Python language becomes more ubiquitous. Number 9 on our countdown is the How to Implement Search Algorithms with Python program from Codecademy.  Linear Search,  Time Complexity of Linear Search, Finding Elements in Lists) Best Case Performance, Worst Case Performance , Average Case Performance. Skill-based training modules include: 1) Linear Search - Imagine that you are a DJ at a party. The diagram on the right shows your playlist for the event. A party guest wants to know if “Uptown Funk” by Bruno Mars is a song on your playlist, 2) Finding Elements in Lists - Linear search can be used to search for a desired value in a list. It achieves this by examining each of the elements and comparing it with the search element starting with the first element to the, 3) Best Case Performance - Linear search is not considered the most efficient search algorithm, especially for lists of large magnitudes. However, linear search is a great choice if you expect to find the target value, 4) Worst Case Performance - There are two worst cases for linear search. Case 1: when the target value, 5) Average Case Performance - If this search was used 1000 times on 1000 different lists, some of them would be the best case, some the worst. For most searches, it would be somewhere in between, 6) Time Complexity of Linear Search - Linear search runs in linear time. Its efficiency can be expressed as a linear function, with the number of comparisons to find a target increasing linearly as the size of the list, N, increases. In the Linear & Binary Search Project - learn to modify a version of binary search to look for data in a sparse dataset.

Enroll today (teams & execs welcome): https://fxo.co/Ccqx 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe)  [https://fxo.co/Ccqx] 

Download your complimentary Python, TensorFlow & PyTorch - Career Transformation Guide.

Graphic source: CareerFoundry

Data Science - Top 10 Countdown of Certification & Training Programs (#9)

Colleagues, the Global Knowledge 2021 IT Salary Survey ranks Google Certified Professional Data Engineer with an average salary of $171,749 USD #1 out of all IT certifications. ZipRecruiter lists some 773,863 Data Scientist positions in the United States alone. Our #9 recommendation on our Top 10 countdown is the Become a Data Architect program. Plan, design and implement enterprise data infrastructure solutions and create the blueprints for an organization’s data management system. You’ll create a relational database with PostGreSQL, design an Online Analytical Processing (OLAP) data model to build a cloud based data warehouse, and design scalable data lake architecture that meets the needs of Big Data. Finally, you will learn how to apply the principles of data governance to an organization’s data management system.With a focus on Data Architecture Foundations you will learn to design a data model, normalize data, and create a professional ERD. Finally, you will take everything you learned and create a physical database using PostGreSQL (Project: Design and HR Database); Designing Data Systems, Data Lake design patterns and how to enable transactional capabilities in a Data Lake (Project: Design an Enterprise Data Lake System); Data Governance - Data Management Architectures, as well as the golden record creation and master data governance processes (Project: Data Governance at Sneakerpeak).

Enroll today (teams & execs welcome): https://tinyurl.com/4mck9jnx 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe)  

Download your complimentary Data Science - Career Transformation Guide.

Graphic source: DreamsTime

Top 10 Machine LearningCertification & Training Programs (#10)

Colleagues, the average salary for a Machine Learning Engineer at $123,524 USD according to Glassdoor. Number 10 in our Top 10 Countdown is the Machine Learning Engineering Career Track Program from Springboard. Learn to deploy ML Algorithms and build your own portfolio. More than 50% of the Springboard curriculum is focused on production engineering skills. In this course, you'll design a machine learning/deep learning system, build a prototype and deploy a running application that can be accessed via API or web service.  The 500+ hour curriculum features a combination of videos, articles, hands-on projects, and career-related coursework.  Skill-based training modules include: 1) Battle-Tested Machine Learning Models, 2) Deep Learning, 3) Computer Vision and Image Processing, 4) The Machine Learning Engineering Stack, 5) ML Models At Scale and In Production, 6) Deploying ML Systems to Production, and 7) Working With Data. You will build a realistic, complete, ML application that’s available to use via an API, a web service or, optionally, a website. One-on-one Mentorship provides you with  weekly guided calls with your personal mentor, an industry expert. Our career coaching calls will help your mentor. Create a successful job search strategy, Build your Machine Learning Engineering network, Find the right job titles and companies, Craft a Machine Learning Engineer resume and LinkedIn profile, Ace the job interview and Negotiate your salary.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe)  [ ]

Down your complimentary AI-ML-DL - Career Transformation Guide.

Graphic source: Mouser

Top 10 Python Developer Certification & Training Programs (#10)

Colleagues, the average salary of a  Full Stack Python Developer is $121,111 according to ZipRecruiter. Number 10 on our countdown is the Python Scripting Certification. This cert program will equip you in NumPy, PandasVariables, Operands,  Expressions, Conditional Statements, Loops, Command Line Arguments, Writing to the Screen; Sequences, File Operations - Python files I/O Functions, Lists and related operations, Tuples and related operations, Strings and related operations, Sets and related operations, Dictionaries,; Functions, OOPs, Modules, Errors and Exceptions, Parameters, Global variables, Variable scope and Returning Values, Lambda Functions, Object Oriented Concepts, Standard Libraries, Modules Used in Python (OS, Sys, Date and Time etc.), Import Statements. Learn different types of sequence structures, related operations, and their usage. Also learn diverse ways of opening, reading, and writing to files. Then create generic python scripts, how to address errors/exceptions in code, and finally how to extract/filter content using regex. Next, cover basics of statistics, different types of measures and probability distributions, and the supporting libraries in Python that assist in these operations. Finally, learn in detail about data visualization - matplotlib library, grids, axes, plots, markers, colors, fonts and styling, types of plots - bar graphs, pie charts, histograms and contour plots. 

Enroll today (teams & execs welcome): https://fxo.co/BMaW 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe) 

Download your complimentary Python, TensorFlow & PyTorch - Career Transformation Guide.

Graphic source: Unstop

Data Science - Top 10 Certification & Training Programs (#10)

Colleagues, the global data science platform market was valued at $31B in 2020, and it is expected to reach $2301 by 2026, registering a CAGR of 39.7 % during the forecast period, 2021-2026 according to Mordor Intelligence. The #10 recommendation on our Top 10 countdown is Spark, Ray and Python for Scalable Data Science from InformIT. Learn to integrate Python and distributed computing, scale data processing with Spark, conduct exploratory data analysis with PySpark, utilize parallel computing with Ray and implement machine learning and artificial intelligence applications with Ray. Skill-based training modules include: 1 - Introduction to Distributed Computing in Python, 2 - Scaling Data Processing with Spark, 3 - Exploratory Data Analysis with PySpark, 4 - Parallel Computing with Ray, and 5 - Scaling AI Applications with Ray. Ray enables you to scale both the evaluation and tuning of our models. You see how Ray makes possible very efficient hyperparameter tuning. You also see how, once you have a trained model, Ray can serve predictions from your machine learning model. Finally, the lesson finishes with an introduction to how Ray can enable you to both deploy machine learning models to production and monitoring.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe)

Download your complimentary Data Science - Career Transformation Guide.

Graphic source: Mesh-AI

PyTorch - Top 3 training programs to advance your AI-ML career

Colleagues, the average salary for a PyTorch Developer is $129,645 according to ZipRecruiter.  Our first recommendation is Introduction to Machine Learning with PyTorch - Supervised Learning - a common class of methods for model construction (Project: Find Donor for CharityML). Second, Deep Learning - learn the foundations of neural network design and training in PyTorch (Project: Build an Image Classifier). And third, Unsupervised Learning - implement unsupervised learning methods for different kinds of problem domains (Project: Create Customer Segments) offered by Udacity. Next, Deep Learning with Tensorflow, Keras and PyTorch - Introduction to Deep Learning and Artificial Intelligence, How Deep Learning Works, High-Performance Deep Learning Networks, Convolutional Neural Networks, and Moving Forward with Your Own Deep Learning Projects from InformIT. And third, Machine Learning with PyTorch - Open Source Torch Library, machine learning, and for deep learning specifically, are presented with an eye toward their comparison to PyTorch, Scikit-learn library, similarity between PyTorch tensors and the arrays in NumPy or other vectorized numeric libraries, clustering with PyTorch, image classifiers from InformIT.

Enroll in one or more programs today (teams & execs welcome): 

• Introduction to Machine Learning with PyTorch

• Deep Learning with Tensorflow, Keras and PyTorch 

• Machine Learning with PyTorch

Download your complimentary Python, TensorFlow & PyTorch - Career Transformation Guide.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe) 

Top 3 Strategies to advance your TensorFlow Developer career

Colleagues, the average salary for a TensorFlow Developer is $132,215 according to ZipRecruiter.  First, Get Certified: A high quality cert from a reputable vendor or professional association may boost your income by 5%-10%. In the Deep Learning with TensorFlow program you will master popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python. Deep Learning with Tensorflow, Keras and PyTorch - build deep learning models in all the major libraries: TensorFlow, Keras, and PyTorch along with artificial neural networks. And Advanced Deployment Scenarios with TensorFlow - gain expertise in TensorFlow Extended, TF Hub, Transfer learning, Inference, Module storage, Text based model, Word embeddings, Experimenting with embeddings, Colab1m, Classify cats and dogs and Transfer learning), 3 - Tensorboard and Federated Learning. Second, Get Published. Write a 1-2 page article on Best Practices or Industry Trends for Medium, LinkedIn Articles or Technology.org. Third, Get Connected. Join the TensorFlow Forum. Sign-up for the TensorFlow Community on GitHub and subscribe to the TensorFlow User Group on LinkedIn.

Enroll in one or more programs today (teams & execs welcome): 

• Deep Learning with TensorFlow

• Deep Learning with Tensorflow, Keras and PyTorch

• Advanced Deployment Scenarios with TensorFlow

Download your complimentary Python, TensorFlow & PyTorch - Career Transformation Guide.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe)  [ ]

Graphic source: Great Learning

Top 3 strategies for Machine Learning career success

Colleagues Fortune Business Insights projects total Machine Learning market growth through 2029 with a 38.8% CAGR .Glassdoor estimates the average salary for a Machine Learning Engineer at $122,963 USD. First, Get Certified: A high quality cert from a reputable vendor or professional association may boost your income by 5%-10%. Our top recommendation is Python Machine Learning Certification Training using Python that equips you with various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes, and Q-Learning. Next is AWS Certified Machine Learning - AWS Machine Learning-Specialty (ML-S) Certification exam, AWS Exploratory Data Analysis covers topics including data visualization, descriptive statistics, and dimension reduction and includes information on relevant AWS services, Machine Learning Modeling. Finally is the Machine Learning Engineer program that teaches you the data science and machine learning skills required to build and deploy machine learning models in production using Amazon SageMaker, Deep Learning Topics within Computer Vision and NLP, Developing Your First ML Workflow, Operationalizing Machine Learning Projects, and a Capstone Project - Inventory Monitoring at Distribution Centers, Second, Get Published. Write a 1-2 page article on Best Practices or Tech Trends for Medium, LinkedIn Articles or Technology.org. Third, Get Connected. Subscribe to the Data School channel on YouTube (200k members). Join Reddit’s Machine Learning group (2.5m members. Then register for the Wolfram Machine Learning discussion forum.

Enroll in one or more programs today (teams & execs welcome): 

• Python Machine Learning Certification Training using Python

• AWS Certified Machine Learning

• Machine Learning Engineer 

Down your complimentary AI-ML-DL - Career Transformation Guide.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe) 

Graphic source: Forbes-Statista