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-applied-data-science-with-python-specialization

The repository curates all my training and study related to Machine Learning with Python at the University of Michigan. The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. 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 popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.

-java-programming-and-software-engineering-fundamentals-specialization

About this Specialization: Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system. Designed for beginners, this Specialization will teach you core programming concepts and equip you to write programs to solve complex problems. In addition, you will gain the foundational skills a software engineer needs to solve real-world problems, from designing algorithms to testing and debugging your programs.

-ml-on-gcp-c1-invoking-machine-learning-apis

08-practical-ml

Coursera Practical Machine Learning

advanced-machine-learning-specialization

Deep Dive Into The Modern AI Techniques. You will teach computer to see, draw, read, talk, play games and solve industry problems.

agile-leadership-specialization

Develop Agile Leadership Skills. Develop agile leadership skills by implementing change management, social psychology, and Agile principles and philosophy in business.

agile-with-atlassian-jira

Atlassian

ai-product-management-specialization

Manage the Design & Development of ML Products. Understand how machine learning works and when and how it can be applied to solve problems. Learn to apply the data science process and best practices to lead machine learning projects, and how to develop human-centered AI products which ensure privacy and ethical standards.

an-introduction-to-programming-the-internet-of-things-iot-specialization

Create Your Own Internet of Things (IoT) Device. Design and create a simple IoT device in just six courses.

applied-data-science-with-python-specialization

This repository to serve as a public record of my 5 courses of study at University of Michigan specialization introduce learners to data science through the python programming language. 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 popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.

applied-machine-learning

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

atom

autoviz

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

azuredatastudio

Azure Data Studio is a data management tool that enables working with SQL Server, Azure SQL DB and SQL DW from Windows, macOS and Linux.

azurenb

Microsoft Azure Notebooks

bayesian-statistics-from-concept-to-data-analysis

Bayesian Statistics: From Concept to Data Analysis by University of California, Santa Cruz About this Course This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach to the more commonly-taught Frequentist approach, and see some of the benefits of the Bayesian approach. In particular, the Bayesian approach allows for better accounting of uncertainty, results that have more intuitive and interpretable meaning, and more explicit statements of assumptions. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. For computing, you have the choice of using Microsoft Excel or the open-source, freely available statistical package R, with equivalent content for both options. The lectures provide some of the basic mathematical development as well as explanations of philosophy and interpretation. Completion of this course will give you an understanding of the concepts of the Bayesian approach, understanding the key differences between Bayesian and Frequentist approaches, and the ability to do basic data analyses.

beakerx

Beaker Extensions for Jupyter Notebook

become-a-software-project-manager

Become a Software Project Manager

bokeh-notebooks

Interactive Web Plotting with Bokeh in IPython notebook

bookrepo

building-web-applications-in-php-coursera-answer-key

business-analytics-specialization

Make Data-Driven Business Decisions. Achieve fluency in business data strategies in four discipline-specific courses.

calculus-single-variable-part-1---functions

About this Course Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences. Distinguishing features of the course include: 1) the introduction and use of Taylor series and approximations from the beginning; 2) a novel synthesis of discrete and continuous forms of Calculus; 3) an emphasis on the conceptual over the computational; and 4) a clear, dynamic, unified approach. In this first part--part one of five--you will extend your understanding of Taylor series, review limits, learn the *why* behind l'Hopital's rule, and, most importantly, learn a new language for describing growth and decay of functions: the BIG O.

cheatsheets

RStudio Cheat Sheets

cloudera-modern-big-data-analysis-with-sql-specialization

This Specialization teaches the essential skills for working with large-scale data using SQL. Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you. Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that’s being generated is too big to be stored there, and it’s growing too quickly to be efficiently stored in commercial data warehouses. Instead, it’s increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable. To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines. This Specialization is designed to provide excellent preparation for the Cloudera Certified Associate (CCA) Data Analyst certification exam. You can earn this certification credential by taking a hands-on practical exam using the same SQL engines that this Specialization teaches—Hive and Impala.

coding-for-everyone-c-and-cplusplus-specialization

Beginner to Programmer — Learn to Code in C & C++. Gain a deep understanding of computer programming by learning to code, debug, and solve complex problems with C and C++.

computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

computer-science-programming-with-a-purpose

y Princeton University About this Course The basis for education in the last millennium was “reading, writing, and arithmetic;” now it is reading, writing, and computing. Learning to program is an essential part of the education of every student, not just in the sciences and engineering, but in the arts, social sciences, and humanities, as well. Beyond direct applications, it is the first step in understanding the nature of computer science’s undeniable impact on the modern world. This course covers the first half of our book Computer Science: An Interdisciplinary Approach (the second half is covered in our Coursera course Computer Science: Algorithms, Theory, and Machines). Our intent is to teach programming to those who need or want to learn it, in a scientific context. We begin by introducing basic programming elements such as variables, conditionals, loops, arrays, and I/O. Next, we turn to functions, introducing key concepts such as recursion, modular programming, and code reuse. Then, we present a modern introduction to object-oriented programming. We use the Java programming language and teach basic skills for computational problem solving that are applicable in many modern computing environments. Proficiency in Java is a goal, but we focus on fundamental concepts in programming, not Java per se. All the features of this course are available for free. It does not offer a certificate upon completion.

computer-vision-basics-in-microsoft-excel

Computer Vision Basics in Microsoft Excel (using just formulas)