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Certificates

Python 3 Programming Specialization – University of Michigan


Final - Python 3 Programming

Python 3 Programming Specialization
2 months specialization – Variables, conditionals, loops, keyword, parameters, list comprehensions, lambda expressions, class inheritance and OpenCV. Lots of practice. Query Internet APIs for data and extract useful information from them. (syllabus)

University of Michigan

Python Basics
This course introduces the basics of Python 3, including conditional execution and iteration as control structures, and strings and lists as data structures. (syllabus)

University of Michigan

Python Basics
Python Functions Files and Dictionaries

Python Functions, File and Dictionaries
This course introduces the dictionary data structure and user-defined functions. You’ll learn about local and global variables, optional and keyword parameter-passing, named functions and lambda expressions. (syllabus)

University of Michigan

Data Collection and Processing with Python
This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. (syllabus)

University of Michigan

Data Collection and Processing With Python
Python Classes and Inheritcane

Python Classes and Inheritance
This course introduces classes, instances, and inheritance. You will learn how to use classes to represent data in concise and natural ways. You’ll also learn how to override built-in methods and how to create “inherited” classes that reuse functionality. (syllabus)

University of Michigan

Python Project: pillow, tesseract, and opencv
This course will walk you through a hands-on project suitable for a portfolio. You will be introduced to third-party APIs and will be shown how to manipulate images using the Python imaging library (pillow), how to apply optical character recognition to images to recognize text (tesseract and py-tesseract), and how to identify faces in images using the popular opencv library. (syllabus)

University of Michigan

Python Project pillow tesseract and opencv

Machine Learning – Stanford University


Python Classes and Inheritcane

Machine Learning – Stanford University
This course introduces classes, instances, and inheritance. You will learn how to use classes to represent data in concise and natural ways. You’ll also learn how to override built-in methods and how to create “inherited” classes that reuse functionality. (syllabus)

University of Michigan

Applied Data Science Python Specialization – University of Michigan


Applied Data Science in Python-1

Applied Data Science with Python
This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance. (syllabus)

University of Michigan

Introduction to Data Science with Python
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. (syllabus)

University of Michigan

Introduction to Data Science in Python
Python Functions Files and Dictionaries

Applied Plotting, Charting & Data Representation in Python
This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. (syllabus)

University of Michigan

Applied Machine Learning in Python
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. (syllabus)

University of Michigan

Data Collection and Processing With Python
Python Classes and Inheritcane

Applied Text Mining in Python
This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. (syllabus)

University of Michigan

Applied Social Network Analysis in Python
This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. (syllabus)

University of Michigan

Python Project pillow tesseract and opencv