www.globalknowledge.com Open in urlscan Pro
52.222.236.115  Public Scan

Form analysis
3 forms found in the DOM

POST /us-en/account/sign-in/

<form action="/us-en/account/sign-in/" class="show-loading-overlay" enctype="multipart/form-data" method="post"><input name="__RequestVerificationToken" type="hidden"
    value="adVEY6cYQ8dm3qnqXMoPdBUPYSooZOsMFLTR6Ik6j3rzce3Lr9kaIZB0Kvuhjio4yiJzfbtF-irAiJZXuVPdFSWb2j81">
  <div class="field email">
    <label>Email Address<span class="required-marker">*</span></label>
    <input class="account-email" id="account-email" name="Username" placeholder="Email Address" type="text" value="">
  </div>
  <div class="field pw">
    <label>Password<span class="required-marker">*</span></label>
    <input class="account-pw" id="account-pw" name="Password" placeholder="Password" type="password">
  </div>
  <input id="ReturnUrl" name="ReturnUrl" type="hidden"
    value="/us-en/course/191058/building-intelligent-applications-with-ai-and-ml-level-1/?utm_source=mkto&amp;utm_medium=email&amp;utm_campaign=SKL_ILT-NA_FY25-ALL-EMLS-DATA_AI_PLE_March&amp;mkt_tok=Nzc4LU5VVS03MTUAAAGSJTJ_DY0ocJ8MuBvoa10LzcNtMe0EXA0Ifa1XL5oGrDJMlhAW7ahKyYlFCgfb0sUS2eWBHcKja2BUk7575UWhyJUHdo9-jTQbbjF8mATMd-EUscXw">
  <div class="account-links">
    <ul>
      <li>
        <a href="/us-en/account/create-account/?returnUrl=%2fus-en%2fcourse%2f191058%2fbuilding-intelligent-applications-with-ai-and-ml-level-1%2f%3futm_source%3dmkto%26utm_medium%3demail%26utm_campaign%3dSKL_ILT-NA_FY25-ALL-EMLS-DATA_AI_PLE_March%26mkt_tok%3dNzc4LU5VVS03MTUAAAGSJTJ_DY0ocJ8MuBvoa10LzcNtMe0EXA0Ifa1XL5oGrDJMlhAW7ahKyYlFCgfb0sUS2eWBHcKja2BUk7575UWhyJUHdo9-jTQbbjF8mATMd-EUscXw&amp;utm_source=mkto&amp;utm_medium=email&amp;utm_campaign=SKL_ILT-NA_FY25-ALL-EMLS-DATA_AI_PLE_March">Create an Account</a>
      </li>
      <li><a href="/us-en/account/forgot-password/?utm_source=mkto&amp;utm_medium=email&amp;utm_campaign=SKL_ILT-NA_FY25-ALL-EMLS-DATA_AI_PLE_March">Forgot Your Password?</a>
      </li>
      <li><a href="https://mygk.globalknowledge.com/" target="_blank">Access MyGK</a>
      </li>
      <li>
      </li>
    </ul>
  </div>
  <div class="button-set">
    <input type="submit" class="btn-secondary" value="Submit">
  </div>
  <input name="ufprt" type="hidden"
    value="6519CC9F61F5D0ADE368C09B47431F33EF647D7159906746582C47537C2D64C99DFC276CA267EBF5328AC435293DD139AF83AB9FE27C9C0109BF84E4C8C44F4B62AB8F25CB586BB6EA34B8830DA696B76572E906C3002BCCFC4FAADFB41970EDF94740E740D3C34ED51DB265E2FC4280DCF5C20FA9B992BB2D9306F6F22A84B7BFC9F26D">
</form>

GET /us-en/search/

<form method="GET" action="/us-en/search/">
  <div class="form-row">
    <div class="select-wrapper">
      <div class="select-label">
        <span class="nav-select-label"> Course&nbsp;&nbsp;<i aria-hidden="true" class="fa fa-caret-down"></i>
        </span>
      </div>
      <select class="nav-search-select " name="f">
        <option value="course">Course</option>
        <option value="certification">Certification</option>
        <option value="article">Article</option>
        <option value="whitePaper">White Paper</option>
        <option value="pastWebinar">Webinar – Recorded</option>
      </select>
    </div>
    <div class="input-wrapper">
      <input type="text" id="nav-search-field" class="search-field" placeholder=" Search" name="q" aria-label=" Search Field" autocapitalize="off" autocomplete="off" autocorrect="off">
    </div>
  </div>
  <input type="submit" class="search-submit">
</form>

POST

<form id="fileUploadForm" enctype="multipart/form-data" method="post" target="fileUploadIframe"><input type="file" id="fileSelector" name="file" style="display: none;"><input name="filename" type="hidden"></form>

Text Content

Your browser is incompatible with this site. Upgrade to a different browser like
Google Chrome or Mozilla Firefox to experience this site.

Buy More, Save More with our exclusive Instructor Led Training Prepay Packages!





MyGK
Support
USA - English
 * USA - English
 * Canada - English
 * Canada - français
 * Worldwide Locations

0
Checkout


CART (0)

Sign In
Email Address*
Password*
 * Create an Account
 * Forgot Your Password?
 * Access MyGK
 * 


Primary Navigation
 * Courses
    * Course Catalog
    * Special Offers
    * Delivery Formats
    * Guaranteed to Run
    * Group Training
    * Skillsoft Codecademy
    * E-Learning
   
   Find Your Course
   
   
   TOPICS
   
    * 5G
    * Agile and Scrum
    * Analytics and Data Management
    * Application Development
    * Artificial Intelligence and Machine Learning
    * Business Analysis
    * Business Skills
    * Cloud Computing
    * Cybersecurity
    * Data Center
   
    * DevOps
    * Enterprise Architecture
    * Enterprise Data Storage
    * IT Policy and Governance
    * IT Service Management
    * Leadership and Management
    * Managing Remote Teams
    * Networking and Wireless
    * Project Management
    * Python
   
    * Unified Communications
    * Virtualization
   
   
   BRANDS
   
    * Adobe
    * Apple
    * AWS
    * Cisco
    * Citrix
    * CompTIA
    * Dell
    * Google Cloud
    * IBM
    * ITIL®
   
    * Juniper Networks
    * Microsoft
    * Microsoft Office
    * Mirantis / Docker
    * Nutanix
    * Oracle
    * Palo Alto Networks
    * PMI
    * Red Hat®
    * ServiceNow
   
    * Veeam
    * VMware
   
   * Course Catalog
   * Special Offers
   * Delivery Formats
   * Guaranteed to Run
   * Group Training
   * Skillsoft Codecademy
   * E-Learning
 * Certifications
   Find Your Certification Path
   
   
   TOPICS
   
    * Agile and Scrum
    * Business Analysis
    * Cloud Computing
    * Cybersecurity
    * DevOps
    * Enterprise Architecture
    * IT Service Management
   
    * Networking and Wireless
    * Project Management
    * Scaled Agile Framework® (SAFe®)
   
   
   BRANDS
   
    * Apple
    * AWS
    * Cisco
    * Citrix
    * CompTIA
    * Google Cloud
    * ITIL
   
    * Juniper
    * Microsoft
    * Mirantis / Docker
    * Nutanix
    * Red Hat
    * ServiceNow
    * Veeam
   
    * VMware
   
   * Certification Training
   * Top-Paying IT Certifications
 * Insights
   * The Value of Training
   * Articles & Resources
   * Training Tools
   * Webinars & Free Courses
   * IT Skills and Salary Report

Course  
Course Certification Article White Paper Webinar – Recorded

Contact Sales
 * Training
    * IT Training Courses
    * Business and IT Certification Training
    * Subscriptions
    * Delivery Formats
    * Training Locations
    * Guaranteed to Run
    * Special Offers
   
   Find Your Course
   
   
   TOPICS
   
    * 5G
    * Agile and Scrum
    * Analytics and Data Management
    * Application Development
    * Artificial Intelligence and Machine Learning
    * Business Analysis
    * Business Skills
    * Cloud Computing
    * Cybersecurity
    * DevOps
   
    * Enterprise Architecture
    * IT Service Management
    * Leadership and Management
    * Managing Remote Teams
    * Networking and Wireless
    * Project Management
    * Python
    * Virtualization
   
   
   BRANDS
   
    * Adobe
    * Apple
    * AWS
    * Cisco
    * Citrix
    * CompTIA
    * Google Cloud
    * IBM
    * (ISC)²
    * ITIL®
   
    * Juniper Networks
    * Microsoft
    * Microsoft Office
    * Mirantis
    * Nutanix
    * Oracle
    * Palo Alto Networks
    * PMI
    * Red Hat®
    * ServiceNow
   
    * Veeam
    * VMware

Support
0
Checkout


CART (0)

Request Group Training


BUILDING INTELLIGENT APPLICATIONS WITH AI AND ML - LEVEL 1

Exclusive - Learn the fundamentals of Artificial Intelligence and Machine
Learning to develop intelligent applications.

Intelligent applications that are developed using Artificial Intelligence and
Machine Learning are helping businesses take critical initiatives. These
applications incorporate the power of predictive and prescriptive analytics,
consumer data, and cutting-edge technologies. They are used by many
organizations and enterprises to automatically discover, learn and give
predictions and recommendations. Examples of such applications include risk
analysis, fraud detection, and prevention, personalized health services, etc.

This course focuses on covering the fundamentals like Statistics, probability,
and a variety of machine learning algorithms that form the building blocks for
the development of intelligent applications.

 * Global Knowledge Delivered Course
 * Training Exclusives

 * Live Instructor
   
   LIVE INSTRUCTOR
   
   Experience live expert-led training in person, from your home, office or
   anywhere with an internet connection.

 * Group Training
   
   GROUP TRAINING
   
   Live expert-led training for your team or entire organization that can be
   customized to fit your exact needs.

 * Virtual Classroom Live (5)

Virtual Classroom Live | May 20 - 22, 2024 | 8:30 AM - 4:30 PM EDT | ONLINE
Virtual Classroom Live | May 20 - 22, 2024 | 8:30 AM - 4:30 PM EDT | ONLINE
Virtual Classroom Live | Jun 24 - 26, 2024 | 8:30 AM - 4:30 PM EDT | ONLINE
Virtual Classroom Live | Jul 08 - 10, 2024 | 8:30 AM - 4:30 PM EDT | ONLINE
Virtual Classroom Live | Sep 23 - 25, 2024 | 8:30 AM - 4:30 PM EDT | ONLINE
Virtual Classroom Live | Nov 11 - 13, 2024 | ONLINE
Start learning as soon as today! Click Add To Cart to continue shopping or Buy
Now to check out immediately.
Access Period:
Scheduling a custom training event for your team is fast and easy! Click here to
get started.

IS THIS THE RIGHT COURSE?

 * Basic familiarity with Python programming.
 * Basic understanding of Data Terminologies.
 * Familiarity with enterprise IT.
 * Foundational knowledge in mathematical concepts like linear algebra and
   probability.
 * Basic linux skills.
 * Basic SQL skills.

WHO SHOULD ATTEND?

This is an introduction-level hands-on course suitable for everyone who wants to
explore the field of Artificial Intelligence (AI) and Machine Learning (ML).
This course covers the foundations of AI, ML, programming, search, and logic
along with their applications to computational problems. This is a level 1
course in building your skills for developing Intelligent applications using
Machine Learning and Artificial Intelligence. Anyone who wants to shift their
career to AI and ML can attend this course such as

 * Business Analysts
 * Data Analysts
 * Developers
 * Administrators
 * Architects
 * Managers
 * Anyone new to AI and ML who wants to understand the foundations of ML and AI
   for developing ML applications.

WHAT YOU'LL LEARN

 * Explore Jupiter notebooks and Python
 * Recall and Remember Statistics and Probability concepts and explore coding in
   Python for data analysis
 * Understand advanced probability concepts and data visualizations using
   libraries such as Matplotlib, seaborn
 * Understand various Machine Learning Algorithms and their applications
 * Understand various Predictive Models
 * Apply Machine Learning algorithms to build predictive models
 * Understand Recommendation Systems
 * Understand how to deal with data in the real world
 * Apply Machine Learning on Big Data using Apache Spark
 * build UI and REST APIs for ML models

COURSE OUTLINE

 1. Getting Started with Jupitor Notebooks and Python
    
    * Installing Python 3.x and Data Science environment
    * Importing required modules
    * Writing and executing Python code in Jupiter notebook
    * Understanding Data Visualizations using Matplotlib and seaborn.
    * Running Python scripts
    * Statistics and Probability Essentials
      
      * Understanding Descriptive and Inferential Statistics and the difference
        between them
      * Understanding Data types - quantitative and qualitative
      * How to understand the spread of data with measures of Central Tendency
        and dispersion
      * Understanding dirty data - missing values and outliers
      * Understanding probability distributions, Probability density function
        and probability mass function
      * Understanding the spread and distribution of data using Python.
      * Introduction to Percentiles and Moments and why they are important?
      * Understanding Hypothesis Testing and various types of Hypothesis tests
        with their applications.
    * Advanced Probability Concepts
      
      * Covariance and Correlation and their role in understanding Data
      * How Conditional Probability helps in predictive analytics?
      * Baye's Theorem and it's applications
 2. Machine Learning Algorithms
    
    * Understanding Different Types of Machine Learning Algorithms - Supervised,
      Semi-Supervised, UnSupervised, Reinforcement Learning
    * Distinguish between Linear and Non-Linear, Distance-based, Parametric and
      Non-Parametric machine learning models
    * Understanding different phases of building Machine Learning Models
    * Differentiate between Classification and Regression
    * An overview of linear and logistic regressions
    * An overview of decision trees and random forests
    * An overview of KNN and SVM
    * How to Build Predictive Models with available data?
      
      * Understanding your data - Data loading and descriptive analysis
      * Dealing with unclean data - Data Cleaning and Pre-processing
      * Building machine learning models with Linear Regression and Logistic
        Regression
      * Understand when to apply Polynomial Regression and build a model
      * Building a predictive model using multivariate regression
      * Multi-level models
 3. Evaluating and Tuning your models with advanced Machine Learning with Python
    
    * Understanding model fit - overfitting and underfitting, Bias-Variance
      Trade-Off
    * Understanding model evaluation metrics for regression and classification
    * Understanding K-fold cross-validation to avoid overfitting
    * Bayesian models
    * Implementing Email spam classifier with Naïve Bayes Classifier
    * Understand K-Nearest Neighbors Algorithm and using KNN for predictive
      analytics
    * Understand Gradient Descent, Stochastic Gradient Descent, and tune your
      model
    * Understand ensemble methods, bagging and boosting
    * Understand various boosting algorithms
    * Unsupervised Machine Learning
      
      * Understanding Clustering
      * Understand K-Means Clustering with a case study
      * Understanding Dimensionality Reduction and Principal Component Analysis
      * Applying PCA on a real world dataset
    * Understanding and Building Recommendation Systems
      
      * What are recommendation Systems
      * Understanding User-based and Item-based Collaborative Filtering
      * Finding similar movies
      * Improving the results of movie similarities
      * Making movie recommendations to people
      * Improving our recommendation results

BUY NOW

PREREQUISITES

 * Basic familiarity with Python programming.
 * Basic understanding of Data Terminologies.
 * Familiarity with enterprise IT.
 * Foundational knowledge in mathematical concepts like linear algebra and
   probability.
 * Basic linux skills.
 * Basic SQL skills.

FOLLOW-ON COURSES

 * Building Intelligent Applications with AI and ML - Level 2

$2195
GK# 821536 Vendor# AL/ML Level 1
Vendor Credits:

Your Selections:
Virtual Classroom Live
3 Days: May 20 - May 22
8:30 AM - 4:30 PM EDT
Location: ONLINE
Access Period:
No available dates
Add To Cart

BUY NOW


Request a quote

 * Send as a prefilled cart
 * Download course details
 * Request custom delivery

FOOTER NAVIGATION

 * 
 * 
 * 
 * 


COMPANY

 * About Us
 * News
 * Awards
 * Channel Partners
 * Support
 * FAQ


SOLUTIONS

 * Value of Training
 * Group Training
 * Training Tools & Resources
 * Industries
 * Government

--------------------------------------------------------------------------------

© 2024 Skillsoft
 * Privacy Notice
 * Legal Terms of Service
 * Cookie-Präferenzen
 * Payment and Policies
 * Our COVID Response




This website uses cookies to enhance your overall experience. By using this
site, you consent to the use of cookies per our privacy statement.




Live chat:Chat with an Expert