Getting a little stressed about a job interview is completely natural. Interviews for programming jobs are a bit different, however, and it’s important to plan accordingly so you have all of your many bases covered. This immersive course was compiled by a team that has conducted hundreds of technical interviews at Google and Flipkart, and will give you not just interview tips, but an in-depth review of all the programming knowledge you’ll need to ace any programming interview.
- Access 83 lectures & 20.5 hours of content 24/7
- Learn how to approach & prepare for coding interviews
- Understand pointer concepts & memory management at a deep & fundamental level
- Tackle a wide variety of linked list problems & know how to answer linked list questions in interviews
- Master a variety of general programming problems that may come up in an interview
- Visualize how common sorting & searching algorithms work
- Gain step-by-step solutions to dozens of programming problems from Game of Life to Sudoku Validator & more
This massive package covers three powerful and versatile testing technologies, as well as the theory and fundamental principles behind software testing. You’ll dive into Sikuli, Selenium, and JUnit to learn not only how to use each, but solve specific, real-world problems with them. Before you know it, you’ll have a real foundation in testing.
- Access 145 lectures & 16.5 hours of content 24/7
- Use image recognition to automate just about anything that appears on-screen w/ Sikuli
- Work w/ Selenium’s Java API to test browser functionality & automate tasks w/ nearly 45 solved examples
- Test user interactions of all kinds such as clicking, entering text, dragging & dropping, & selecting from dropdowns
- Interact w/ HTML5 based elements like video players
- Write simple tests using all the different features of JUnit tests
This course lies at the intersection of four areas: math, finance, computer science, and business. Over this enormous course, you’ll cover risk modeling, factor analysis, numerical optimization, and linear and logistic regression by looking at real financial models and examples.
- Access 130 lectures & 14.5 hours of content 24/7
- Model risk using covariance matrices & historical returns
- Calculate Value-at-Risk & understand the implications, strengths, & weaknesses of this approach
- Understand principal components, Eigen values, Eigen vectors, & Eigenvalue decomposition
- Apply PCA to explain the returns of a tech stock like Apple
- Understand the classic linear programming problem setup & the primal & dual problems
- Explore the method of least squares
- Implement multiple regression in Excel, R, & Python
- Discover applications of logistic regression, as well as the link to linear regression & machine learning
Big Data describes the methodology used by major and minor corporations alike to manage and derive insight from enormous amounts of data. Some of the most important tools for working with Big Data are Hadoop, Spark, Apache Storm, and QlikView, all of which you’ll learn in detail over this course.
- Access 120 lectures & 7 hours of content 24/7
- Install Hadoop in standalone, pseudo-distributed, & fully distributed modes
- Customize your MapReduce jobs
- Learn how to leverage the power of TDDs & dataframes to manipulate data w/ ease in Spark
- Understand the building blocks of every Apache Storm topology: Spouts & Bolts
- Run a Storm topology in the local mode & the remote mode
- Cover the Qlikview In-memory data model
- Use list boxes, table boxes, & chart boxes to query data in Qlikview
- Access 212 lectures & 21 hours of content 24/7
- Install & set up a basic web server w/ jQuery & jQuery UI libraries
- Cover the basics, advanced topics, & plugins of jQuery
- Explore AngularJS in depth, including custom directives for template expansion, DOM manipulation, scope inheritance, & more
- Discover the React component lifecycle, the component mounting, updating & unmounting phases, & more
- Learn about React in production environments
This course brings together two of the hottest technologies out there today in TensorFlow and the Google Cloud Platform. TensorFlow is an open source software library for machine intelligence, while the Google Cloud Platform delivers cloud computing solutions. Bring these two together and you get this course in which you’ll learn how to deliver machine learning algorithms over the cloud.
- Access 87 lectures & 15.5 hours of content 24/7
- Explore TensorFlow & Cloud ML on the Google Cloud Platform
- Discuss Google’s vision, NLP, & translate APIs on the cloud
- Learn about neural networks for learning functions
- Discover linear regression, logistic regression, image classification, & working w/ images in TensorFlow
- Get an introduction to machine learning principles like K-nearest neighbors, decision trees, & more
Learn from history, or be condemned to repeat it. That goes double in the world of tech! Why did GroupOn, Yahoo, and MySpace stumble while AirBnB, Google, and Facebook thrived? This course seeks to answer questions like this, studying the past two decades to summarize some key trends of the tech industry. It rounds off with some specific ideas on how an individual or a company may deal with these trends.
- Access 20 lectures & 3.5 hours of content 24/7
- Explore trends from 1994-2003, 2003-2008, 2005 to today, 2008-2012, 2012 to today, & 2008 to today
- Analyze today’s biggest trends: Big Data, cloud computing, & machine learning
- Learn from the mistakes of tech history
The Google Cloud Platform is not the most popular cloud offering out there (hello AWS!) but it may be the best cloud offering for high-end machine learning applications. That’s because TensorFlow, the extremely popular deep learning technology is also from Google. This comprehensive guide to TensorFlow and the Google Cloud Platform will help put you on certification track to become a Google Data Engineer or Cloud Architect.
- Access 166 lectures & 22 hours of content 24/7
- Cover the material you need to pass Google Data Engineer & Cloud Architect certification exams
- Explore AppEngine, Kubernetes, & Compute Engine
- Discuss Big Data & Managed Hadoop w/ Dataproc, Dataflow, BigTable, BigQuery, & more
- Learn what neural networks & deep learning are, how neurons work, & how neural networks are trained
- Understand DevOps principles like StackDrive logging, monitoring, & cloud deployment management
- Discover security, networking, & Hadoop foundations
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