Accomplish­ments

Docker and Kubernetes: The Big Picture

PluralSight Aug 2019 – Aug 2019
Docker and Kubernetes are transforming the application landscape - and for good reason. This course is the perfect way to get yourself – and your teams – up to speed and ready to take your first steps.
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Extracting Structured Data from the Web Using Scrapy

PluralSight Aug 2019 – Aug 2019
Data analysts and scientists are always on the lookout for new sources of data, competitive intelligence, and new signals for proprietary models in applications. The Scrapy package in Python makes extracting raw web content easy and scalable.
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Angular: The Big Picture

PluralSight Sep 2018 – Sep 2018
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Using Databases with Python by University of Michigan on Coursera

Coursera Feb 2017 – Mar 2017
This course will introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course will use SQLite3 as its database. We will also build web crawlers and multi-step data gathering and visualization processes. We will use the D3.js library to do basic data visualization. This course will cover Chapters 14-15 of the book “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-13 of the textbook and the first three courses in this specialization. This course covers Python 3.
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Machine Learning by Stanford University on Coursera

Coursera Feb 2017 – Mar 2017
This course provides a broad introduction to 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). The course will also draw from numerous case studies and applications, so that you’ll 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.
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Using Python to Access Web Data by University of Michigan on Coursera

Coursera Jan 2017 – Feb 2017
This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python. This course will cover Chapters 11-13 of the textbook “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization. These topics include variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files. This course covers Python 3.
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Top RATED

UPWORK Jan 2017 – Dec 2019
You earn ´Top Rated´ status by building an impressive reputation on Upwork. You must have a proven history of success with multiple clients, delight your clients every time with high-quality work, and contribute to a safe and vibrant marketplace by knowing and following the Upwork Terms of Service.
Top Rated status helps outstanding freelancers and agencies grow their businesses and become even more successful in the Upwork marketplace. When you earn this status, you’ll be recognized through a badge on your profile and rewarded with exclusive perks, including increased access to client projects.
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