Data Science Fundamentals LiveLessons teaches you the foundational concepts, theory, and techniques you need to know to become an effective data scientist. The videos present you with applied, example-driven lessons in Python and its associated ecosystem of libraries, where you get your hands dirty with real datasets and see real results.

Description

If nothing else, by the end of this video course you will have analyzed a number of datasets from the wild, built a handful of applications, and applied machine learning algorithms in meaningful ways to get real results. And along the way you learn the best practices and computational techniques used by a professional data scientist. More specifically, you learn how to acquire data that is openly accessible on the Internet by working with APIs. You learn how to parse XML and JSON data to load it into a relational database.

About the Instructor

Jonathan Dinu is an author, researcher, and most importantly, an educator. He is currently pursuing a Ph.D. in Computer Science at Carnegie Mellon’s Human Computer Interaction Institute (HCII), where he is working to democratize machine learning and artificial intelligence through interpretable and interactive algorithms. Previously, he founded Zipfian Academy (an immersive data science training program acquired by Galvanize), has taught classes at the University of San Francisco, and has built a Data Visualization MOOC with Udacity. In addition to his professional data science experience, he has run data science trainings for a Fortune 500 company and taught workshops at Strata, PyData, and DataWeek (among others). He first discovered his love of all things data while studying Computer Science and Physics at UC Berkeley, and in a former life he worked for Alpine Data Labs developing distributed machine learning algorithms for predictive analytics on Hadoop.

Jonathan has always had a passion for sharing the things he has learned in the most creative ways he can. When he is not working with students, you can find him blogging about data, visualization, and education at hopelessoptimism.com or rambling on Twitter @jonathandinu.

Skill Level

• Beginner

What You Will Learn

• How to get up and running with a Python data science environment
• The essentials of Python 3, including object-oriented programming
• The basics of the data science process and what each step entails
• How to build a simple (yet powerful) recommendation engine for Airbnb listings
• Where to find quality data sources and how to work with APIs programmatically
• Strategies for parsing JSON and XML into a structured form
• The basics of relational databases and how to use an ORM to interface with them in Python
• Best practices of data validation, including common data quality checks

Who Should Take This Course

• Aspiring data scientists looking to break into the field and learn the essentials necessary
• Journalists, consultants, analysts, or anyone else who works with data and looking to take a programmatic approach to exploring data and conducting analyses
• Quantitative researchers interested in applying theory to real projects and taking a computational approach to modeling.
• Software engineers interested in building intelligent applications driven by machine learning
• Practicing data scientists already familiar with another programming environment looking to learn how to do data science with Python

Course Requirements

• Basic understanding of programming
• Familiarity with Python and statistics are a plus

Lesson Descriptions

Lesson 1: Introduction to Data Science with Python

Lesson 1 begins with a working definition of data science (as we use it in the course), gives a brief history of the field, and provides motivating examples of data science products and applications. This lesson covers how to get set up with a data science programming environment locally, as well as gives you a crash course in the Python programming language if you are unfamiliar with it or are coming from another language such as R. Finally, it ends with an overview of the concepts and tools that the rest of the lessons cover to hopefully motivate you for and excite you about what’s to come!

Lesson 2: The Data Science Process—Building Your First Application

Lesson 2 introduces the data science process by walking through an end-to-end example of building your very first data science application, an AirBnB listing recommender.

You continue to learn how to work with and manipulate data in Python, without any external libraries yet, and leverage the power of the built-in Python standard library. The core application of this lesson covers the basics of building a recommendation engine and shows you how, with simple statistics and a little ingenuity, you can build a compelling recommender, given the right data. And finally, it ends with a formal treatment of the data science process and the individual steps it entails.

Lesson 3: Acquiring Data—Sources and Methods

Lesson 3 begins the treatment of each of the specific stages of the data science process, starting with the first: data acquisition. The lesson covers the basics of finding the appropriate data source for your problem and how to download the datasets you need once you have found them.

Starting with an overview of how the infrastructure behind the Internet works, you learn how to programmatically make HTTP requests in Python to access data through APIs, as well as the basics of two of the most common data formats: JSON and XML. The lesson ends by setting up the dataset we use for the rest of the course: Foursquare Venues.

Working with the Foursquare dataset, you learn how to interact with APIs and do some minor web scraping. You also learn how to find and acquire data from a variety of sources and keep track of its lineage all along the way. You learn to put yourself in the data science mindset and how to see the data (hidden in plain sight) that we interact with every day.

Lesson 4: Adding Structure—Data Parsing and Storage

Lesson 4 picks up with the second stage of what traditionally is referred to as an extract, transform, and load (ETL) pipeline, adding structure through the transformation of raw data.

You see how to work with a variety of data formats, including XML and JSON, by parsing the data we have acquired to eventually load it into an environment better-suited to exploration and analysis: a relational database. But before we load our data into a database, we take a short diversion to talk about how to conceptually model structure in data with code. You get a primer in object-oriented programming and learn how to leverage it to create abstractions and data models that define how you can interface with your data.

Lesson 5: Storing Data: Relational Databases (with SQLite)

Lesson 5 starts with an introduction to one of the most ubiquitous data technologies—the relational database. The lesson serves as an end cap to the ETL pipeline of the previous videos. You learn the ins and outs of the various strategies for storing data and see how to map the abstractions you created in Python to database tables through the use of an object-relational mapper (ORM). By being able to query and manipulate data with Python while persisting data in a database reliably, the interface ORMs provide gives you the best of both worlds.

Lesson 6: Data Validation and Exploration

Lesson 6 starts by showing you how to effectively query your data to understand what it contains, uncover any biases it might contain, and learn the best practices of dealing with missing values. After you have validated the quality of the data, you use descriptive statistics to learn how your data is distributed as well as learn the limits of point statistics (or rather single number estimates) and why it is often necessary to use visual techniques.

About LiveLessons Video Training

The LiveLessons Video Training series publishes hundreds of hands-on, expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. This professional and personal technology video series features world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, IBM Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include: IT Certification, Programming, Web Development, Mobile Development, Home and Office Technologies, Business and Management, and more. View all LiveLessons on InformIT at: http://www.informit.com/livelessons

About MIT horizon

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

3+ Hours of Video Instruction

Video instruction, demonstrations of Amazon Web Services and third-party cloud solutions provide a clear guide to understanding networking with Amazon Virtual Private Cloud.

Overview

Networking in Amazon Web Services (AWS) LiveLessons reviews key concepts related to networking, how those concepts apply to Amazon Virtual Private Cloud, and how networking enables high availability, fault tolerance, performance, and security. AWS Certified Solutions Architect Professional and AWS Authorized Instructor Richard A. Jones covers concepts and methods necessary to design and build secure networks within Amazon Web Services (AWS).

For applications running on EC2, the architecture begins with the network; in AWS, that is the Virtual Private Cloud or VPC. In order to gain the highest degree of security, resiliency, and performance, you need to design the network accordingly. In this series of videos from Richard A. Jones, you learn how network design can help leverage multiple availability zones and how the application of routing, network access control lists, and security groups contribute to security. You also see how to extend on-premises networks into AWS with VPN and Direct Connect, review how to achieve the best performance, and much more.

Gaining an in-depth understanding of the concepts unique to cloud computing is essential for being a valuable asset to any business leveraging AWS for their computing and storage needs.

Topics include:

• Networking Review
• Amazon VPC Part 1: Basics
• Amazon VPC Part 2: Advanced Concepts
• Network Security
• Connecting VPCs and On-Premises Networks
• Performance and Other Notes

Skill Level

• Intermediate

Learn How To

• Leverage multiple availability zones via network design
• Contribute to security via application of routing, network access control lists, and security groups
• Extend on-premises networks into AWS with VPN and Direct Connect and achieve the best performance

Who Should Take This Course

• Working solutions architects, network administrators, and system administrators looking to understand and implement Amazon Virtual Private Cloud within their AWS infrastructure

Course Requirements

• Basic understanding of AWS, including definitions of regions and availability zones

Lesson Descriptions

Lesson 1, “Networking Review,” reviews fundamental knowledge needed throughout the use of AWS VPC, IPv4, and IPv6 addresses as well as classless-interdomain routing, and C.I.D.R notation as a way of specifying ranges of IP addresses.

Lesson 2, “Amazon VPC Part 1: Basics,” discusses Amazon Virtual Private Cloud and how subnets enable the use of multiple availability zones as well as routing, internet access, and how public IP addresses can be allocated and assigned to EC2 instances.

Lesson 3, “Amazon VPC Part 2: Advanced Concepts,” demonstrates how to keep EC2 instances private and protected from the internet while still allowing egress only, or one-way internet access. Review network address translation, third-party virtual network appliances, and VPC endpoints.

Lesson 4, “Network Security,” discusses network security and demonstrates the use of network access control lists and security groups. Amazon VPC provides all the tools needed to create a secure network, but responsibility is needed to use those tools appropriately.

Lesson 5, “Connecting VPCs and On-Premises Networks,” reviews VPC peering, various VPN solutions, and AWS Direct Connect. While isolated networks like Amazon VPC provide powerful means of controlling network traffic and protecting instances, there are plenty of use cases where resources in VPCs need access to resources in other VPCs or on-premises.

Lesson 6, “Performance and Other Notes,” reviews how to achieve the best network performance with Amazon VPC with the knowledge of other features and options. With a rich collection of enablement and security tools, it is capable of high performance.

About Pearson Video Training

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at  http://www.informit.com/video.

About MIT horizon

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

Amazon Machine Learning LiveLessons is designed to provide a solid foundational understanding of the data preparation and evaluation that’s necessary to run predictive analysis with Machine Learning models. The course covers the concepts necessary to understand Amazon Machine Learning and teaches the user how to leverage the benefits of predictive analysis. Usage scenarios are provided to inspire viewers to create their own value-added services on top of Amazon Machine Learning.

Amazon Machine Learning LiveLessons contains more than 20 independent video lessons totaling more than 3 hours of instruction with demos, interactive labs, and detailed slide explanations. Hands-on labs with Amazon Machine Learning are included to provide necessary context and experience to create pragmatic applications. Viewers will walk away with a solid understanding of how Amazon Machine Learning is structured and how to apply it in their own scenarios.

Asli Bilgin’s knowledge comes from her unique experience working at Amazon and as a Machine Learning consultant for her business, Nokta Consulting. She uses her professional skills for her personal vintage jewelry business, oyacharm. She is an award-winning cloud computing executive who has more than two decades of experience working for companies such as Dell, Microsoft, and Amazon. She specializes in IT transformation and modernization leveraging disruptive technologies. At Amazon, Asli created, launched, and ran the global Software as a Service program and ran the Financial Services IT Transformation practice for AWS Professional Services. At Microsoft, she led the cloud and web strategy for 80 countries in the Middle East and Africa, based out of Dubai. In her early career, Asli served as a software developer, technical manager, and architect for large and complex enterprise projects.

Topics include
Module 1: Amazon Machine Learning Basics
Module 2: Amazon Machine Learning Data Architecture
Module 3: Data and Schema Configuration
Module 4: Machine Learning Visualization and Modeling
Module 5: Predictions with Amazon Machine Learning

Learn How To

• Understand the concepts, taxonomy, and principles behind Machine Learning
• Get started with the core Amazon Machine Learning service
• Solve for personalization, search, marketing, finance, productivity, and management efficiency using AML
• Configure a schema, and set up a data source using “small data” in S3
• Use data insights and visualization tools
• Leverage Features, Targets, Observations, Labeled Data, Unlabeled Data, and Ground Truth to prepare historical data for predictive analysis
• Prepare data for use in a regression model and a multi-class model
• Evaluate and refine Amazon ML model
• Use predictions

Who Should Take This Course

IT technologists and hobbyists, computer science students, and domain experts who want to understand the basic principles of Amazon Machine Learning and its application and receive a hands-on practical demonstration of using Amazon Machine Learning. You don’t have to be a data scientist or professional developer to benefit from this course. In fact, small business owners who have a firm handle on their own business data would find value in the examples used, which is a retail business and small dataset.

Course Requirements Familiarity with technology consoles and administrative interfaces would be very helpful. A rudimentary understanding of the Amazon Web Services platform would be a bonus, but not necessary to learn from this course. A basic understanding of how data and its schema is structured digitally would be an asset to understanding the concepts of Machine Learning.

Module Descriptions

Module 1, “Amazon Machine Learning Basics,” discusses understanding how Amazon ML works and how you can frame problem sets. By the end, the first data set will be uploaded.

Module 2, “Amazon Machine Learning Data Architecture,” covers how to set up the source from SQL Server. The data to be downloaded will be provided, so SQL Server does not need to be installed.

In Module 3, “Data and Schema Configuration,” historical sales data is used to predict the future price of an item. “Gotchas” are showcased so a solid starting machine learning model can be built.

Module 4, “Machine Learning Visualization and Modeling,” uses data insights to further refine the model.

Module 5, “Predictions with Amazon Machine Learning,” examines predictions and determining future data. The model’s performance is analyzed, and real-time and batch predictions are applied. Finally, key concepts, questions to consider, and next steps are covered.

About Pearson Video Training

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more.

About MIT horizon

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

More than 6.5 hours of video instruction to help you learn the skills necessary to implement security in an Amazon Web Services (AWS) Cloud environment.

AWS Cloud Security LiveLessons explores Amazon Web Services (AWS), which offers a scalable cloud computing platform designed for high availability and reliability, providing the tools that allow you to run a wide range of applications. Helping to protect the confidentiality, integrity, and availability (CIA) of your systems and data is of the utmost importance. The AWS infrastructure has been architected to be one of the most flexible and secure cloud computing environments available today. It is designed to provide an extremely scalable, highly reliable platform that allows customers to deploy applications and data quickly and securely.

This course first covers the basics and rapid deployment capabilities of AWS to build a knowledge foundation for individuals who are brand new to cloud computing and AWS. You will explore the methods that AWS uses to secure their cloud services. You will learn how you, as an AWS customer, can have the most secure cloud solution possible for a wide variety of implementation scenarios. This course delves into the flexibility and agility needed to implement the most applicable security controls for your business functions in the AWS environment through deploying varying degrees of restrictive access to environments based on data sensitivity.

Through onscreen demos and detailed instruction, seasoned presenter Michael J. Shannon takes you through the key facets of AWS best practices and services in the areas of shared security and compliance; identity and access management; infrastructure security; data protection; and logging and monitoring to ensure that your AWS environment remains secure.

Topics include:

• AWS Security Fundamentals
• AWS Shared Security Responsibility Model
• AWS Compliance Services
• Understanding Users and Credentials
• Identity and Access Management (IAM)
• NACLs and Security Groups
• AWS WAF and AWS Shield
• Cryptographic Services
• Key Management
• Visibility and Reporting

Skill Level

Intermediate systems/network/application professional

Learn How To

• Apply security concepts, models, and services in an AWS environment
• Manage user account credentials and deploy AWS Identity and Access Management (IAM) to manage access to AWS services and resources securely
• Protect your network through best practices using NACLs and security groups, as well as the security offered by AWS Web Application Firewall (WAF) and AWS Shield
• Protect your data with IPsec, AWS Certificate Manager, AWS Key Management Services (KMS), AWS CloudHSM, and other key management approaches
• Ensure that your AWS environment is secure through logging, monitoring, auditing, and reporting services available in AWS

Who Should Take This Course

• Existing certified cloud practitioners interested in building a strong security foundation to enhance their experience with Amazon EC2, VPC, and many other services
• Individuals preparing for the AWS Solutions Architect, Developer, and SysOps Administrator Associate certifications
• Anyone moving into or advancing in the IT and Information Security field

Course Requirements

Requires basic knowledge of cloud networking and network security concepts and technologies.

Lesson descriptions

Lesson 1, AWS Security Fundamentals, covers security fundamentals including understanding the CIA triad; examining types and categories of controls; reviewing core AWS Services; and surveying common threats to AWS services.

Lesson 2, AWS Shared Security Responsibility Model, covers the very important AWS shared security responsibility model. Topics include: understanding the shared security responsibility model; establishing AWS responsibilities, including security of and in the cloud. Finally, this lesson concludes with a look at strategies when planning for security.

Lesson 3, AWS Compliance Services, is all about AWS compliance services. You will learn about the AWS premium support services; understand risk and compliance; and look at a case study of HIPAA security and compliance.

Lesson 4, Understanding Users and Credentials, explores users and credentials as well as the account root user. In addition, you’ll learn to configure user accounts and credentials; learn about password policies; and review Identity and Access Management (IAM) best practices

Lesson 5, Identity and Access Management (IAM), looks deeper at the AWS IAM service. You will first learn the basics of IAM; explore IAM users and groups; IAM roles; managed and custom Policies; and examine IAM Federated Services, the AWS Security Token Service (STS); and wrap up with a look at AWS Cognito.

Lesson 6, NACLs and Security Groups, covers network access control lists (NACLs)and security groups with a focus on understanding security zoning, network segmentation, and best Practices for network security in the cloud.

Lesson 7, AWS WAF and AWS Shield, focuses on having a working knowledge of the mechanics of and working with the AWS Web Application Firewall (WAF) and AWS Shield. The lesson explores distributed denial of service (DDoS) protection and response; the AWS WAF Advanced API; deploying malware protection best practices; and surveying layered defense in the cloud.

Lesson 8, Cryptographic Services, covers the basics of cryptographic services; IPsec fundamentals, IPsec in AWS; and AWS Certificate Manager.

In Lesson 9, Key Management, explores AWS Key Management Services (KMS); how to protect EC2 key pairs; how to use encrypted EBS volumes; how to work with Server-Side Encryption (SSE) in S3; and concludes with a look at AWS CloudHSM Security.

Lesson 10, Logging and Monitoring, covers topics including visibility and reporting; security reporting and logging in AWS; activating Flow Logs and Region-based CloudTrail; AWS Auditing; Pre-Audit Tasks, and concludes with a look at additional security services offered in an AWS environment.

About Pearson Video Training

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more.

About MIT horizon

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

The PTE Academic Certified Associates Program Training is a comprehensive and informative short course that covers the basics of the Pearson Test of English – Academic (PTE Academic).  In 45 minutes you will learn more about how tests are booked, the test day procedure, the test format, how to provide results to institutions, and more. After completing the course, you’ll become a PTE Academic Certified Associate and will be ready to inform your clients about the test.

About this course

The Reading section of the test has 5 different item types with a total of 15-18 items. It requires test takers to understand texts written in English and respond to prompts under timed conditions. In this module, you will be introduced to the Reading section of PTE Academic and the skills that are tested. Teachers must understand the five item types in this section of the test and the basic instructions learners must know to complete tasks. You will also revisit some of the key features of extracting information from and identifying meaning in text.

About this course

The Writing section of the test requires test takers to use standard academic writing conventions to respond to one or more prompts under timed conditions. In this module, you will be introduced to the writing section of PTE Academic and the skills that are tested. Teachers must understand the two item types in the Writing section of the test and the basic instructions learners must know to complete tasks. You will also revisit some of the key features of English grammar, vocabulary, coherence, and critical thinking.

About this course

This module will introduce you to the Speaking section of PTE Academic and the skills that are tested. This section of PTE Academic requires test takers to respond orally under timed conditions using fluent speech, correct pronunciation, including word and sentence stress, and intonation. Teachers must understand the five item types in the Speaking section of the test and the responses required from test takers. You will also revisit some of the key features of English pronunciation and oral fluency, while getting some valuable guidance on how to prepare test takers for this section of the test.

About this course

In this module, you will be introduced to the key features of PTE Academic and the skills that are tested in each part of the test. This will include an outline of the process of registering for the test, taking the test and accessing the scores. You will also learn about the scoring method for the test and how automated scoring is used for Speaking and Writing responses.