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The Computer Science Advancement Bundle

Course Summary

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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    Course Syllabus

    • Introduction
    • Pointer and Arrays
    • Strings are just pointers at heart
    • Linked lists can be fun!
    • Bit Manipulation
    • General programming problems - practice makes perfect
    • Big-O Notation, Sorting And Searching Algorithms
    • Recursion and the recursive sense
    • Stacks And Queues
    • Binary Trees
    • Binary Search Trees
    • Binary Tree Problems
    • Heaps
    • Revisiting Sorting - The Heap Sort
    • Heap Problems
    • Graphs
    • Graph Algorithms
    • Shortest Path Algorithms
    • Spanning Tree Algorithms
    • Graph Problems
    • Introducing Sikuli
    • Getting Stuff Done
    • Language Constructs
    • More Language Constructs
    • Sikuli and Java
    • Unusual Use-cases and Smart Sikuli
    • Introducing Selenium
    • Understanding Selenium
    • Setting up your Testing Environment
    • Locating Elements in a WebPage
    • Testing and Automating User Interactions
    • Automating Browser Navigation Actions
    • Windows, Frames and Alerts
    • WebDrivers for Different Browsers
    • Capturing Screenshots
    • Listening to Events and Executing JavaScript
    • Building Maintainable Scripts using the Page Object Model
    • Extending Selenium
    • Automating Interactions with HTML5 elements
    • Cross Browser Testing with Selenium Grid
    • HTML and CSS primer
    • Introducing JUnit
    • Getting Started with JUnit Tests and Assertions
    • Granular Checks with Matchers
    • Assumptions
    • Fixtures
    • Working with Different TestRunners
    • Controlling Test Behavior with Rules
    • Mockito : The Mock Object Framework
    • Introducing the Principles of Software Testing
    • Principles of Software Testing
    • The Systems Development Life Cycle (SDLC)
    • Static Testing
    • Dynamic Testing
    • Testing Processes
    • You, This Course and Us
    • Introducing Risk management
    • Outlining an Approach to Risk Management
    • RIsk Modeling in Excel/VBA
    • Risk Modeling in R
    • Risk Modeling in Python
    • Introducing Factor Analysis
    • Factor Analysis and PCA
    • Basic Statistics Required for PCA
    • Diving into Principal Components Analysis
    • PCA in Excel
    • PCA in R
    • PCA in Python
    • Introducing Numerical Optimisation
    • Linear Programming and the Simplex Method
    • Implementing Linear Programming in Excel
    • Implementing Linear Programming In R
    • Implementing Linear Programming in Python
    • Understanding Integer Programming
    • Implementing Integer Programming in Excel
    • Implementing Integer Programming in R
    • Implementing Integer Programming in Python
    • Introducing Linear and Logistic Regression
    • Connect the Dots with Linear Regression
    • Basic Statistics Used for Regression
    • Simple Regression
    • Applying Simple Regression
    • Multiple Regression
    • Applying Multiple Regression using Excel
    • Logistic Regression for Categorical Dependent Variables
    • Solving Logistic Regression
    • Applying Logistic Regression
    • Introduction
    • Why is Big Data a Big Deal
    • Installing Hadoop in a Local Environment
    • The MapReduce "Hello World"
    • Run a MapReduce Job
    • Juicing your MapReduce - Combiners, Shuffle and Sort and The Streaming API
    • HDFS and Yarn
    • MapReduce Customizations For Finer Grained Control
    • Introduction
    • Introduction to Spark
    • Resilient Distributed Datasets
    • Advanced RDDs: Pair Resilient Distributed Datasets
    • Advanced Spark: Accumulators, Spark Submit, MapReduce , Behind The Scenes
    • Introduction
    • Stream Processing with Storm
    • Implementing a Hello World Topology
    • Processing Data using Files
    • Running a Topology in the Remote Mode
    • Adding Parallelism to a Storm Topology
    • Section 7: Building a Word Count Topology
    • Remote Procedure Calls Using Storm
    • Managing Reliability of Topologies
    • Integrating Storm with Different Sources/Sinks
    • Using the Storm Multilang Protocol
    • Introduction
    • Getting Started
    • Loading Data into a QV App
    • Exploring Data using the UI
    • Transforming Data in Load Scripts
    • Effectively presenting data
    • Advanced Load Transformations
    • Appendix
    • You, This Course and Us
    • Introducing jQuery
    • Introduction To jQuery
    • Install And Set Up
    • Selectors
    • Some Loose Ends
    • Event Handling
    • CSS And Animations
    • DOM Manipulation
    • Ajax Requests
    • Performance Optimizations
    • Plugins
    • The Widget Factory
    • The jQuery UI Library
    • Introducing Angular
    • Introduction To Angular
    • Install And Setup
    • Basic Overview Of Angular Components
    • Controllers: Digging Deeper
    • Services: Digging Deeper
    • Scopes And Scope Inheritance
    • Built-In And Custom Directives
    • Directives And Isolated Scopes
    • Behind The Scenes: $watch, $apply and $digest
    • Expressions
    • Filters
    • Forms And Validation
    • Directives: Digging Deeper
    • Behind The Scenes: Dependency Injection
    • The Final Stretch
    • Introducing React
    • Introduction
    • Install and Set up
    • React Basics
    • JSX and the Babel Compiler
    • React Components
    • State and Props: Immutable Props
    • State and Props: The Component as a State Machine
    • Synthetic Events in React
    • Bringing It All Together in A Single Application
    • The React Component Lifecycle
    • Mixins
    • ES Syntactic Sugar
    • Forms
    • Miscellaneous
    • React In Production
    • Animations
    • Routing
    • One Last Thing…
    • Introduction To Google Cloud Platform
    • TensorFlow and Machine Learning
    • Regression in TensorFlow
    • Vision, Translate, NLP and Speech: Trained ML APIs
    • Machine Learning Algorithms
    • Solving Classification Problems
    • Association Detection
    • Dimensionality Reduction
    • Sentiment Analysis
    • Decision Trees
    • A Few Useful Things to Know About Overfitting
    • Random Forests
    • Recommendation Systems
    • Introduction
    • From Dotcom Bubble to the Financial Crisis
    • From the Financial Crisis to the Present
    • Today and Tomorrow
    • You, This Course and Us
    • Introduction
    • Compute Choices
    • Storage
    • Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS
    • The Hadoop Ecosystem
    • BigTable ~ HBase = Columnar Store
    • Datastore ~ Document Database
    • BigQuery ~ Hive ~ OLAP
    • Dataflow ~ Apache Beam
    • Dataproc ~ Managed Hadoop
    • Pub/Sub for Streaming
    • Datalab ~ Jupyter
    • TensorFlow and Machine Learning
    • Regression in TensorFlow
    • Vision, Translate, NLP and Speech: Trained ML APIs
    • Networking
    • Ops and Security

Course Fee:
USD 25

Course Type:


Course Status:



1 - 4 hours / week

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