Learning Management
Informatica Online Training Informatica Certification Course Edureka
Problem statement: A Bank's management committee wants to understand their business needs, customer's requirement in detail and more accurate manner. They want to build up one Decision support system in which they want some banking report on daily, weekly, monthly basis. The vendor needs to use their database to give an automatic reporting application for present and future requirements. Using Informatica PowerCenter you have to fulfill all the requirements. Problem statement: Target Mega Mart is planning to build a data warehouse of sales, to enhance their decision support.
Quantitative Trading Analysis with Python Udemy
It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or take decisions as DIY investor. Learning quantitative trading analysis is indispensable for finance careers in areas such as quantitative research, quantitative development, and quantitative trading mainly within investment banks and hedge funds. It is also essential for academic careers in quantitative finance. And it is necessary for DIY investors' quantitative trading research and development. But as learning curve can become steep as complexity grows, this course helps by leading you step by step using index replicating fund historical data for back-testing to achieve greater effectiveness.
Modern Robotics, Course 2: Robot Kinematics Coursera
About this course: Do you want to know how robots work? Are you interested in robotics as a career? Are you willing to invest the effort to learn fundamental mathematical modeling techniques that are used in all subfields of robotics? If so, then the "Modern Robotics: Mechanics, Planning, and Control" specialization may be for you. This specialization, consisting of six short courses, is serious preparation for serious students who hope to work in the field of robotics or to undertake advanced study.
If You Can Cook You Can Code Vol 5: Artificial Intelligence
Kevin Kelly has stated that AI is going to make even bigger changes to the economy than the internet. If you missed out on the internet dot com bubble of the late 90s and early 2000s, now is your chance. AI is coming, and it's coming fast. And AI is also one of the most difficult things to learn. Once you get past a Wikipedia article the next step is a 1000 page textbook that will take a year to read plus learning a bunch of new fields of math and programming.
Python GUI Programming Solutions Udemy
Python is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a scripting language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Its flexible syntax enables developers to write short scripts while at the same time being able to use object-oriented concepts to develop very large projects. This course follows a task-based approach to help you create beautiful and very effective GUIs with the least amount of code necessary.
Python Data Visualization Solutions Udemy
Effective visualization can help you get better insights from your data, and help you make better and more informed business decisions. This video starts by showing you how to set up matplotlib and other Python libraries that are required for most parts of the course, before moving on to discuss various widely used diagrams and charts such as Gantt Charts. As you will go through the course, you will get to know about various 3D diagrams and animations. As maps are irreplaceable to display geo-spatial data, this course will show you how to build them. In the last section, we'll take you on a thorough walkthrough of incorporating matplotlib into various environments and how to create Gantt charts using Python.
Data Acquisition and Manipulation with Python Udemy
Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. In this course, you'll start by learning how to acquire data from the web in its already "clean" format, such as in a .csv You'll then learn to transform this data so it's in its most useful format for analysis. After that, you'll dive into data aggregation and grouping, where you'll learn to group similar data for easier analysis purposes. From there, you'll be shown different methods of web scraping using Python.
Applied Data Science Capstone Coursera
About this course: This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about why data cleaning and munging is an important part of data science and how it occupies more than 80% of a data scientist's daily work. You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code.
Hybrid Python3 Swift4 Applications Udemy
BI-RADS DATA SCIENCE FOR SWIFT/PYTHON HACKERS, is a course designed by an iOS Developer for iOS and Python Developers. You will learn iPython enough to implement algorithms used in Data Science with little effort. As a Swift Programmer you will find the syntax needed to flow through iPython in Jupyter a breeze!!! After grasping a thorough knowledge of supervised learning in the first two sections, you will dive into xCode and write a Logistic Regression Binary Based application. In your final project, you will build BIRADS, a Breast Imaging-Reporting and Data System that takes the output data from a Neural Network and assigns a BI-RADS Category given input from the following features...
Natural Language Processing with Python and NLTK
Natural Language Processing (NLP) is a hot topic into the Machine Learning field. This course is focused in practical approach with many examples and developing functional applications. This course starts explaining you, how to get the basic tools for coding and also making a review of the main machine learning concepts and algorithms. After that this course offers you a complete explanation of the main tools in NLP such as: Text Data Assemble, Text Data Preprocessing, Text Data Visualization, Model Building and finally developing NLP applications. In this course you will find a concise review of the theory with graphical explanations and for coding it uses Python language and NLTK library.