572 Courses

Overview This comprehensive course on Building Big Data Pipelines with PySpark MongoDB and Bokeh will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Building Big Data Pipelines with PySpark MongoDB and Bokeh comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Building Big Data Pipelines with PySpark MongoDB and Bokeh. It is available to all students, of all academic backgrounds. Requirements Our Building Big Data Pipelines with PySpark MongoDB and Bokeh is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 7 sections • 25 lectures • 05:04:00 total length •Introduction: 00:10:00 •Python Installation: 00:03:00 •Installing Third Party Libraries: 00:03:00 •Installing Apache Spark: 00:12:00 •Installing Java (Optional): 00:05:00 •Testing Apache Spark Installation: 00:06:00 •Installing MongoDB: 00:04:00 •Installing NoSQL Booster for MongoDB: 00:07:00 •Integrating PySpark with Jupyter Notebook: 00:05:00 •Data Extraction: 00:19:00 •Data Transformation: 00:15:00 •Loading Data into MongoDB: 00:13:00 •Data Pre-processing: 00:19:00 •Building the Predictive Model: 00:12:00 •Creating the Prediction Dataset: 00:08:00 •Loading the Data Sources from MongoDB: 00:17:00 •Creating a Map Plot: 00:33:00 •Creating a Bar Chart: 00:09:00 •Creating a Magnitude Plot: 00:15:00 •Creating a Grid Plot: 00:09:00 •Installing Visual Studio Code: 00:05:00 •Creating the PySpark ETL Script: 00:24:00 •Creating the Machine Learning Script: 00:30:00 •Creating the Dashboard Server: 00:21:00 •Source Code and Notebook: 00:00:00

Learn Python Programming using a Step By Step Approach with 200+ code examples.

Scala is doubtless one of the most in-demand skills for data scientists and data engineers. This competitive course will teach you the essential concepts and methodologies of Scala with a lot of practical implementations.

Overview This comprehensive course on Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is this course for? There is no experience or previous qualifications required for enrolment on this Python for Data Analysis. It is available to all students, of all academic backgrounds. Requirements Our Python for Data Analysis is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 19 sections • 99 lectures • 00:08:00 total length •Welcome & Course Overview: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:37:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method ..: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00 •Resources- Python for Data Analysis: 00:00:00

Duration 5 Days 30 CPD hours This course is intended for This course is intended for anyone responsible for conf iguring, maintaining, and troubleshooting Symantec Data Loss Prevention. Additionally, this course is intended for technical users responsible for creating and maintaining Symantec Data Loss Prevention policies and the incident response structure. Overview At the completion of the course, you will be able to: Enforce server, detection servers, and DLP Agents as well as reporting, workflow, incident response management, policy management and detection, response management, user and role administration, directory integration, and filtering. This course is designed to provide you with the fundamental know ledge to configure and administer the Symantec Data Loss Prevention Enforce platform. Introduction to Symantec Data Loss Prevention Symantec Data Loss Prevention overview Symantec Data Loss Prevention architecture Navigation and Reporting Navigating the user interface Reporting and analysis Report navigation, preferences, and features Report filters Report commands Incident snapshot Incident Data Access Hands-on labs: Become familiar with navigation and tools in the user interface. Create, filter, summarize, customize, and distribute reports. Create users, roles, and attributes. Incident Remediation and Workflow Incident remediation and w orkf low Managing users and attributes Custom attribute lookup User Risk Summary Hands-on labs: Remediate incidents and configure a user?s reporting preferences Policy Management Policy overview Creating policy groups Using policy templates Building policies Policy development best practices Hands-on labs: Use policy templates and policy builder to configure and apply new policies Response Rule Management Response rule overview Configuring Automated Response rules Configuring Smart Response rules Response rule best practices Hands-On Labs: Create and use Automated and Smart Response rules Described Content Matching DCM detection methods Hands-on labs: Create policies that include DCM and then use those policies to capture incidents Exact Data Matching and Directory Group Matching Exact data matching (EDM) Advanced EDM Directory group matching (DGM) Hands-on labs: Create policies that include EDM and DGM, and then use those policies to capture incident Indexed Document Matching Indexed document matching (IDM) Hands-on labs: Create policies that include IDM rules and then use those policies to capture incidents Vector Machine Learning Vector Machine Learning (VML) Hands-on labs: Create a VML profile, import document sets, and create a VML policy Network Monitor Review of Network Monitor Protocols Traffic filtering Network Monitor best practices Hands-On Labs: Apply IP and L7 filters Network Prevent Network Prevent overview Introduction to Network Prevent (Email) Introduction to Network Prevent (Web) Hands-On Labs: Configure Network Prevent (E-mail) response rules, incorporate them into policies, and use the policies to capture incidents Mobile Email Monitor and Mobile Prevent Introduction to Mobile Email Monitor Mobile Prevent overview Configuration VPN configuration Policy and Response Rule Creation Reporting and Remediation Troubleshooting Network Discover and Network Protect Network Discover and Network Protect overview Configuring Discover targets Configuring Box cloud targets Protecting data Auto-discovery of servers and shares Running and managing scans Reports and remediation Network Discover and Network Protect best practices Hands-on labs: Create and run a filesystem target using various response rules, including quarantining Endpoint Prevent Endpoint Prevent overview Detection capabilities at the Endpoint Configuring Endpoint Prevent Creating Endpoint response rules Viewing Endpoint Prevent incidents Endpoint Prevent best practices Managing DLP Agents Hands-on labs: Create Agent Groups and Endpoint response rules, monitor and block Endpoint actions, view Endpoint incidents, and use the Enforce console to manage DLP Agents Endpoint Discover Endpoint Discover overview Creating and running Endpoint Discover targets Using Endpoint Discover reports and reporting features Hands-on labs: Create Endpoint Discover targets, run Endpoint Discover targets, and view Endpoint Discover incidents Enterprise Enablement Preparing for risk reduction Risk reduction DLP Maturity model System Administration Server administration Language support Incident Delete Credential management Troubleshooting Diagnostic tools Troubleshooting scenario Getting support Hands-on labs: Interpret event reports and traffic reports, configure alerts, and use the Log Collection and Configuration tool Additional course details: Nexus Humans Symantec Data Loss Prevention 14.0 - Administration training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Symantec Data Loss Prevention 14.0 - Administration course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Introducing the Sales and Marketing with ChatGPT bundle, a powerhouse of knowledge and tools designed to propel your business towards unprecedented growth and success. This comprehensive package offers a range of valuable resources to enhance your marketing efforts. Harness the cutting-edge capabilities of ChatGPT, an AI-powered tool that revolutionises productivity and customer engagement. With automated tasks, content generation, and seamless customer interactions, ChatGPT is a game-changer for your marketing strategy. Elevate your business with the Sales and Marketing with ChatGPT bundle. Refine your persuasive techniques through Sales Training, master SEO for top rankings, and unleash compelling Copywriting Secrets. Craft impactful email campaigns with the Email Marketing Masterclass. Acquire essential knowledge and tools for success in sales and marketing. Invest in this comprehensive bundle to supercharge your brand and embrace new heights of achievement. The CPD Accredited eight courses are: Course 01: ChatGPT for Marketing and Productivity with AI Tools Course 02: ChatGPT Complete Guide with Expertise Course 03: Project on Deep Learning - Artificial Neural Network Course 04: Learn AI with Python Course 05: Sales Training Course 06: SEO - Search Engine Optimisation Course 07: Copywriting Secrets Course 08: Email Marketing Masterclass Learning Outcomes: By completing this bundle, you will: Refine persuasive techniques for remarkable sales results. Master SEO strategies for top search engine rankings. Craft compelling copy that drives conversions. Harness AI tools to automate tasks and enhance marketing productivity. Create impactful email campaigns that resonate with subscribers. Supercharge your business with advanced marketing skills. The Sales and Marketing with ChatGPT bundle is the ultimate package designed to empower you with a comprehensive skill set and essential tools to excel in the dynamic world of sales and marketing. Let's dive into what this bundle includes: ChatGPT for Marketing and Productivity with AI Tools: Revolutionise your marketing and productivity with ChatGPT. Harnessing the power of artificial intelligence, it automates tasks, generates compelling content, and enhances customer engagement. ChatGPT streamlines processes and delivers exceptional customer experiences from chatbots to content creation. ChatGPT Complete Guide with Expertise: Discover how to create captivating chatbots, generate content, and engage customers, propelling your marketing efforts to the next level. Project on Deep Learning - Artificial Neural Network: Apply your AI knowledge practically with a real-world project focused on artificial neural networks. Gain hands-on experience in deep learning, allowing you to tackle complex marketing challenges with data-driven solutions. Learn AI with Python: Acquire practical AI skills using Python, including data analysis, machine learning, and predictive analytics. Understand how AI can be integrated into marketing strategies for data-driven decision-making. Sales Training: Elevate your sales game with expert Sales Training. Refine your persuasive techniques, master communication and negotiation skills, and build strong customer relationships. Gain confidence, close deals, and achieve remarkable sales results. SEO - Search Engine Optimisation: Achieve top search engine rankings and enhance your online visibility with SEO. Learn the techniques and strategies to optimise your website, increase organic traffic, and effectively reach your target audience. Master the art of SEO, from keyword research to on-page and off-page optimisation, and dominate search engine rankings. Copywriting Secrets: Master the art of persuasive copywriting and captivate your audience with compelling messages that drive conversions. Unlock the power of words to elevate your marketing campaigns and achieve remarkable results. Email Marketing Masterclass: Master the art of highly effective email marketing campaigns that resonate with subscribers. Boost open rates, click-through rates, and drive conversions with expert insights on engaging subject lines, personalisation, and automation techniques. CPD 50 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This bundle is for: Sales professionals Marketing professionals Copywriters Business owners and entrepreneurs Marketing managers Individuals are seeking advanced sales and marketing skills. Requirements Without any formal requirements, you can delightfully enrol in this bundle. Study for the bundle using any internet-connected device, such as a computer, tablet, or mobile device. Career path This bundle opens career paths in: Sales and Business Development Digital Marketing Marketing Management Entrepreneurship AI and Marketing Technology AI Product Manager AI Content Strategist Virtual Assistant Developer Customer Support Automation Specialist Please note that salaries can range from £25,000 to £70,000 annually. Certificates CPD Quality Standard Certificate Digital certificate - £4.99 Hardcopy Certificate (FREE UK Delivery) Hard copy certificate - £9.99 Hardcopy Transcript: £9.99

Learn to use cutting-edge language models ChatGPT, Dalle-2, and Midjourney to create high-quality written content and generative art in this course. Discover how to fine-tune these models for specific tasks and explore the ethical implications and future-proofing strategies for using AI in your work.

In this compact intermediate-level course, you will learn how to use Facebook Prophet to do time series analysis and forecasting. You will learn how Prophet works under the hood and the Prophet API. We will apply Prophet to a variety of datasets, including store sales and stock prices.

Overview This comprehensive course on Microsoft Azure Cloud Concepts will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Microsoft Azure Cloud Concepts comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Microsoft Azure Cloud Concepts. It is available to all students, of all academic backgrounds. Requirements Our Microsoft Azure Cloud Concepts is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 1 sections • 29 lectures • 03:33:00 total length •Unit 01: What will you learn and Cloud Concepts: 00:18:00 •Unit 02: Core Azure architectural components: 00:18:00 •Unit 03: LAB Create a Windows and Linux VM Computer: 00:10:00 •Unit 04: LAB Container creation: 00:04:00 •Unit 05: Storage with Azure: 00:04:00 •Unit 06: LAB Create a storage account: 00:07:00 •Unit 07: Network concepts: 00:03:00 •Unit 08: Lab Network Peering: 00:16:00 •Unit 09: Lab scale set: 00:11:00 •Unit 10: Marketspace and Serverless: 00:07:00 •Unit 11: Event HUB and Logic APPS: 00:07:00 •Unit 12: DevOps Overview: 00:04:00 •Unit 13: Azure Databases Overview: 00:04:00 •Unit 14: Lab SQL: 00:08:00 •Unit 15: What are AI and machine learning: 00:10:00 •Unit 16: Powershell and CLI: 00:09:00 •Unit 17: Azure Advisor: 00:05:00 •Unit 18: Review Core Azure: 00:04:00 •Unit 19: Azure security compliance and trust: 00:03:00 •Unit 20: Lab DDOS and NSGs: 00:07:00 •Unit 21: Authentication and Authorisation: 00:07:00 •Unit 22: Azure security centre: 00:06:00 •Unit 23: LAB Azure key vault and AIP overview: 00:06:00 •Unit 24: Azure Advanced Threat Protection (Azure ATP): 00:06:00 •Unit 25: Azure monitoring: 00:05:00 •Unit 26: Manage Azure Governance: 00:07:00 •Unit 27: Azure privacy and compliance: 00:04:00 •Unit 28: Summary: 00:03:00 •Unit 29: Azure Pricing and support: 00:10:00

This course does not require any prior knowledge of Apache Spark or Hadoop. The author explains Spark architecture and fundamental concepts to help you come up to speed and grasp the content of this course. The course will help you understand Spark programming and apply that knowledge to build data engineering solutions.