113 Natural Language Processing (NLP) courses delivered Online

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up 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 Essentials 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 Python for Data Analysis using NumPy 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 Python for Data Analysis using Pandas 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 Python for Data Visualization using matplotlib 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 Python for Data Visualization using Seaborn 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 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks 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 Capstone Project - Python for Data Analysis & Visualization 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 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model 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 Python for Machine Learning - scikit-learn - Logistic Regression Model 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 Python for Machine Learning - scikit-learn - K Nearest Neighbors 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 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests 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 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) 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 Python for Machine Learning - scikit-learn - K Means Clustering 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 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) 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 Recommender Systems with Python - (Additional Topic) 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 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) 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 Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

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Python for Data Analysis & Visualization Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Python for Machine Learning - scikit-learn - Logistic Regression Model Python for Machine Learning - scikit-learn - K Nearest Neighbors Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Python for Machine Learning - scikit-learn - K Means Clustering Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Recommender Systems with Python - (Additional Topic) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Course 07: Data Analysis in Excel Level 3 Course Modifying a Worksheet Working with Lists Analyzing Data Visualizing Data with Charts Using PivotTables and PivotCharts Working with Multiple Worksheets and Workbooks Using Lookup Functions and Formula Auditing Automating Workbook Functionality Creating Sparklines and Mapping Data Forecasting Data Course 08: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Introduction Prepaid Expenses Models: Resources Download Accounting for Prepaid Expenses Excel Formulas Detailed: Introduction to three Excel Models Formula Based Prepaid Expenses Model Calculate Prepaid Expenses Amortisation from Exact Start Date Prepaid Expenses Summary with Power Query and Pivot Table Advanced VBA Prepaid Expenses Amortisation Model BONUS: Dynamic Dashboard for Divisional Profit and Loss statements: Easy Way Power Query & Pivot Tables based Dashboard without any Formulas, Fully Dynamic Thankyou Course 09: GDPR Data Protection Level 5 Module 01: GDPR Basics Module 02: GDPR Explained Module 03: Lawful Basis for Preparation Module 04: Rights and Breaches Module 05: Responsibilities and Obligations Course 10: Level 3 Cyber Security FUNDAMENTALS OF NETWORKING GETTING STARTED WITH CYBER SECURITY LET'S BEGIN - 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PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) Curriculum of the Bundle Course 01: SQL Server for Beginners Introduction Setup Basic queries Security MSSQL and different drivers Files General Course 02: Microsoft SQL Server Development for Everyone Introduction Manipulating Tables and Data Relationships Foreign Keys Group By and Aggregate Functions Advanced Server Objects and Concepts Course 03: Python for Data Analysis Welcome, Course Introduction & overview, and Environment set-up Python Essentials Python for Data Analysis using NumPy Python for Data Analysis using Pandas Python for Data Visualization using matplotlib Python for Data Visualization using Seaborn Python for Data Visualization using pandas Python for interactive & geographical plotting using Plotly and Cufflinks Capstone Project - Python for Data Analysis & Visualization Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Python for Machine Learning - scikit-learn - Logistic Regression Model Python for Machine Learning - scikit-learn - K Nearest Neighbors Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Python for Machine Learning - scikit-learn - K Means Clustering Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Recommender Systems with Python - (Additional Topic) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Course 04: Coding with HTML, CSS, & Javascript Welcome HTML 5 CSS 3 Bootstrap Project 1 - Design a Landing Page Project 2 - Business Website SProject 3 - Portfolio Course 05: Modern Web Designing - Level 2 Module: 01 1.1 Intro 1.2 Install the Tools and Get Started Module: 02 2.1 Intro to HTML 2.2 What is HTML 2.3 Start a New HTML File & Use Tags 2.4 Header Tags 2.5 Edit Text 2.6 Links 2.7 Images 2.8 Lists 2.9 Challenge 2.10 HTML Outro Module: 03 3.1 CSS Intro 3.2 Add CSS Styles 3.3 Classes and IDs 3.4 Borders 3.5 Sizing 3.6 Padding and Margin 3.7 Text Styles 3.8 DIVs 3.9 Postioning 3.10 Hover 3.11 Easily Center Elements 3.12 Fonts 3.13 Challenge 3.14 CSS Outro Module: 04 4.1 Intro to Bootstrap 4.2 Install Bootstrap 4.3 Indenting and Containers 4.4 The Grid System 4.5 Images 4.6 Buttons 4.7 Challenge 4.8 Bootstrap Outro Module: 05 5.1 Landing Page Intro 5.2 Sketch Your Landing Page 5.3 The Top Section 5.4 Polish the Top Section 5.5 Adding Images 5.6 The Main Points Section 5.7 Collecting Emails With an Opt-In Form 5.8 Challenge 5.9 Landing Page Outro Module: 06 6.1 Business Site Intro 6.2 Sketch Up 6.3 Using Fancy Font Logo 6.4 Carousel Basics 6.5 Carousel Extras 6.6 Text on Images 6.7 Phone Number Icon 6.8 Google Maps 6.9 Font Awesome 6.10 Challenge 6.11 Business Site Outro Module: 07 7.1 Intro 7.2 Portfolio Sketch 7.3 Jumbotron 7.4 Nav Bar 7.5 Panels 7.6 Challenge 7.7 Portfolio Outre Module: 08 8.1 Hosting 8.2 Bluehost 8.3 Uploading 8.4 Tips 8.5 Hosting Outro Course 06: Diploma in PHP Web Development Unit 01: Introduction Unit 02: Environment Configuration Unit 03: PHP Basics and Syntax Unit 04: PHP Forms and MySQL and User Authentication Course 07: Front End Web Development Diploma Welcome to the course! Web Development Basics - HTML Advanced HTML Concepts Introduction to Cascading Style Sheets (CSS) Advanced CSS JavaScript for Begeinners More JavaScript Concepts Getting Started with jQuery More jQuery Bootstrap Basics Project #2 - Pipboy from Fallout 4 Project #3 - Google Chrome Extension BONUS - Coding Another Google Chrome Extension Course 08: Secure Programming of Web Applications Section 01: Introduction Section 02: Well-known Vulnerabilities and Secure Programming Section 03: Conclusion and Summary Course 09: Linux for Absolute Beginners! Introduction to Linux Linux Installation Linux Command Line Interface (CLI) Essentials Advanced CLI Usage Linux Development Tools Web Development Project Web Server Setup, Host Cofiguration and App Deployment Linux User Management Linux Network Administration Course 10: Ethical Hacking Introduction to Ethical Hacking Reconnaissance - Surveying the Attack Surface Scanning and Enumeration - Getting Down to Business Network Presence Attacking Web Hacking Social Engineering - Hacking Humans Course 11: Creativity and Problem Solving Skills Getting Started The Problem Solving Method Information Gathering Problem Definition Preparing for Brainstorming Generating Solutions (I) Generating Solutions (II) Analyzing Solutions Selecting a Solution Planning Your Next Steps Recording Lessons Learned CPD 135 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this SQL (Structured Query Language) bundle. Persons with similar professions can also refresh or strengthen their skills by enrolling in this course. Students can take this course to gather professional knowledge besides their study or for the future. Requirements Our SQL (Structured Query Language) 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 expertise will increase the value in your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (SQL Server for Beginners) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

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

This comprehensive course will help you learn the basics to advanced mechanisms of chatbot development using deep learning with Python. This course is a complete package for beginners to learn chatbot fundamentals with deep learning and its applications and build it from scratch using deep learning (RNNs) with Python.

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This Database Administrator Bundle Consists of the following Premium courses: Course 01: Introduction to Data Analysis Course 02: Data Center Training Essentials: General Introduction Course 03: Data Analytics with Tableau Course 04: Basic Google Data Studio Course 05: Complete Google Analytics Course Course 06: Python for Data Analysis Course 07: Data Analysis in Excel Level 3 Course Course 08: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Course 09: GDPR Data Protection Level 5 Course 10: Level 3 Cyber Security Course 11: Encryption Course 12: Windows 10 Pro Complete Training Course 13: Functional Skills IT Course 14: Learning Computers and Internet Level 2 Benefits you'll get choosing Apex Learning: Pay once and get lifetime access to 14 CPD courses Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID for the title course included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative modules designed by expert instructors Learn at your ease - anytime, from anywhere Study the course from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills Gain valuable knowledge without leaving your home How will I get my Certificate? 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Curriculum of Bundle Course 01: Introduction to Data Analysis Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding Course 02: Data Center Training Essentials: General Introduction Module 01: Data Center Introduction Module 02: Data Center Reliability Module 03: Data Center Equipment Module 04: Data Center White Space Module 05: Data Center Support Spaces Module 06: Data Center Security, Safety, Networks and IT Course 03: Data Analytics with Tableau Module 01: Introduction to the Course Module 02: Project 1: Discount Mart (Sales and Profit Analytics) Module 03: Project 2: Green Destinations (HR Analytics) Module 04: Project 3: Superstore (Sales Agent Tracker) Module 05: Northwind Trade (Shipping Analytics) Module 06: Project 5: Tesla (Stock Price Analytics) Module 07: Bonus: Introduction to Database Concepts Module 08: Tableau Stories Course 04: Basic Google Data Studio Module 01: Introduction to GDS Module 02: Data Visualization Module 03: Geo-visualization Module 04: A Socio-Economic Case Study Course 05: Complete Google Analytics Course Module 01: Overview Module 02: Navigation and Admin Module 03: Creating a New Google Analytics Account Module 04: Website Account Creation Module 05: Connecting To WordPress Website Module 06: Connecting To HTML Site Module 07: Connect Custom Page and Site Builders Module 08: Setting Up Annotations Module 09: Setting Up Intelligence Events Module 10: Set Up Custom Segments Module 11: Export Data for Analysis Module 12: Set Up Custom Reports Module 13: Set Up Google Integrations Module 14: Google Analytics Templates Module 15: Real Time Reporting Module 16: Setting Up Goals Module 17: Third Party Integrations Module 18: Audience Menu Overview Module 19: Interests and Geography Module 20: Conclusion Course 06: Python for Data Analysis Welcome, Course Introduction & overview, and Environment set-up Python Essentials Python for Data Analysis using NumPy Python for Data Analysis using Pandas Python for Data Visualization using matplotlib Python for Data Visualization using Seaborn Python for Data Visualization using pandas Python for interactive & geographical plotting using Plotly and Cufflinks Capstone Project - Python for Data Analysis & Visualization Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Python for Machine Learning - scikit-learn - Logistic Regression Model Python for Machine Learning - scikit-learn - K Nearest Neighbors Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Python for Machine Learning - scikit-learn - K Means Clustering Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Recommender Systems with Python - (Additional Topic) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Course 07: Data Analysis in Excel Level 3 Course Modifying a Worksheet Working with Lists Analyzing Data Visualizing Data with Charts Using PivotTables and PivotCharts Working with Multiple Worksheets and Workbooks Using Lookup Functions and Formula Auditing Automating Workbook Functionality Creating Sparklines and Mapping Data Forecasting Data Course 08: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Introduction Prepaid Expenses Models: Resources Download Accounting for Prepaid Expenses Excel Formulas Detailed: Introduction to three Excel Models Formula Based Prepaid Expenses Model Calculate Prepaid Expenses Amortisation from Exact Start Date Prepaid Expenses Summary with Power Query and Pivot Table Advanced VBA Prepaid Expenses Amortisation Model BONUS: Dynamic Dashboard for Divisional Profit and Loss statements: Easy Way Power Query & Pivot Tables based Dashboard without any Formulas, Fully Dynamic Thankyou Course 09: GDPR Data Protection Level 5 Module 01: GDPR Basics Module 02: GDPR Explained Module 03: Lawful Basis for Preparation Module 04: Rights and Breaches Module 05: Responsibilities and Obligations Course 10: Level 3 Cyber Security FUNDAMENTALS OF NETWORKING GETTING STARTED WITH CYBER SECURITY LET'S BEGIN - THE FUNDAMENTALS OF CYBER SECURITY DIVING DEEP INTO CYBER SECURITY TYPES OF ACTORS, ATTACKS, MALWARE AND RESOURCES FIREWALLS AND ANTIVIRUS KEY SECURITY CONCEPTS Course 11: Encryption Section 01: Introduction Section 02: Basics of Common Encryption Section 03: Technical Aspects of Encryption Section 04: AES Basic Tech Demo Section 05: File and System Encryption Section 06: Conclusion Course 12: Windows 10 Pro Complete Training Module 01: Course Overview Module 02: Building Your Virtual Lab Environment Module 03: Upgrading Windows 7, 8, or 8.1 to Windows 10 Module 04: Building a Microsoft Server 2016 Domain Module 05: Windows Deployment Services (WDS) Module 06: Windows 10 Firewall, Windows Defender and UAC Module 07: Networking Module 08: Troubleshooting Module 09: User Preferences Module 10: Maintenance Course 13: Functional Skills IT Section 1: Introduction Section 2: Information Technology Section 3: Components of IT Section 4: Hardware Section 5: Operating System Section 6: Application/Software Section 7: Networking Section 8: Security Section 9: Traffic Flow & Enterprise Level IT Components Section 10: Storage Section 11: Database Section 12: Virtualisation & Cloud Section 13: Management & Other IT Jobs Course 14: Learning Computers and Internet Level 2 Module 01 : Computer Operating and Troubleshooting Module 02 : Internet and Computing - Key Applications Module 03 : Internet and Computing - Tools & Networking Module 04 : Windows 8 for PC Module 05 : Windows 10 - New Developments Module 06 : Cyber Security Awareness CPD 160 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Database Administrator bundle. Requirements Our Database Administrator course is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. Career path Having this Database Administrator expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included P.S. The delivery charge inside the UK is £3.99, and the international students have to pay £9.99.

Give a compliment to your career and take it to the next level. This Web Application Penetration Testing & Security will provide you with the essential knowledge and skills required to shine in your professional career. Whether you want to develop skills for your next job or want to elevate skills for your next promotion, this Web Application Penetration Testing & Security will help you keep ahead of the pack. The Web Application Penetration Testing & Security incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can reinforce your professional skills and essential knowledge, reaching out to the level of expertise required for your position. Further, this Web Application Penetration Testing & Security will add extra value to your resume to stand out to potential employers. 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Benefits you'll get choosing Apex Learning for this Web Application Penetration Testing & Security: One payment, but lifetime access to 11 CPD courses Certificate, student ID for the title course included in a one-time fee Full tutor support available from Monday to Friday Free up your time - don't waste time and money travelling for classes Accessible, informative modules taught by expert instructors Get 24/7 help or advice from our email and live chat teams Learn at your ease - anytime, from anywhere Study the course from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificates: Free (Previously it was £10*11= £110) Hard Copy Certificates: Free (Previously it was £20*11= £220) Curriculum of the Bundle Course 01: Complete Web Application Penetration Testing & Security Unit 01: Introduction Unit 02: BE PREPARED Unit 03: WEB APPLICATION TECHNOLOGIES Unit 04: INFORMATION GATHERING - MAPPING THE APPLICATIONS Unit 05: CROSS-SITE SCRIPTING ATTACKS - XSS Unit 06: SQL INJECTION ATTACKS - EXPLOITATIONS Unit 07: CROSS SITE REQUEST FORGERY - XSRF Unit 08: AUTHENTICATION & AUTHORIZATION ATTACKS Unit 09: CLIENT SIDE SECURITY TESTING Unit 10: FILE RELATED VULNERABILITIES Unit 11: XML EXTERNAL ENTITY ATTACKS - XXE Course 02: Secure Programming of Web Applications Section 01: Introduction Section 02: Well-known Vulnerabilities and Secure Programming Section 03: Conclusion and Summary Course 03: GDPR Data Protection Level 5 Module 01: GDPR Basics Module 02: GDPR Explained Module 03: Lawful Basis for Preparation Module 04: Rights and Breaches Module 05: Responsibilities and Obligations Course 04: Front End Web Development Diploma Welcome to the course! Web Development Basics - HTML Advanced HTML Concepts Introduction to Cascading Style Sheets (CSS) Advanced CSS JavaScript for Begeinners More JavaScript Concepts Getting Started with jQuery More jQuery Bootstrap Basics Project #2 - Pipboy from Fallout 4 Project #3 - Google Chrome Extension BONUS - Coding Another Google Chrome Extension Course 05: Modern Web Designing - Level 2 Module: 01 1.1 Intro 1.2 Install the Tools and Get Started Module: 02 2.1 Intro to HTML 2.2 What is HTML 2.3 Start a New HTML File & Use Tags 2.4 Header Tags 2.5 Edit Text 2.6 Links 2.7 Images 2.8 Lists 2.9 Challenge 1 2.10 HTML Outro Module: 03 3.1 CSS Intro 3.2 Add CSS Styles 3.3 Classes and IDs 3.4 Borders 3.5 Sizing 3.6 Padding and Margin 3.7 Text Styles 3.8 DIVs 3.9 Postioning 3.10 Hover 3.11 Easily Center Elements 3.12 Fonts 3.13 Challenge 3.14 CSS Outro Module: 04 4.1 Intro to Bootstrap 4.2 Install Bootstrap 4.3 Indenting and Containers 4.4 The Grid System 4.5 Images 4.6 Buttons 4.7 Challenge 3 4.8 Bootstrap Outro Module: 05 5.1 Landing Page Intro 5.2 Sketch Your Landing Page 5.3 The Top Section 5.4 Polish the Top Section 5.5 Adding Images 5.6 The Main Points Section 5.7 Collecting Emails With an Opt-In Form 5.8 Challenge 4 5.9 Landing Page Outro Module: 06 6.1 Business Site Intro 6.2 Sketch Up 6.3 Using Fancy Font Logo 6.4 Carousel Basics 6.5 Carousel Extras 6.6 Text on Images 6.7 Phone Number Icon 6.8 Google Maps 6.9 Font Awesome 6.10 Challenge 4 6.11 Business Site Outro Module: 07 7.1 Intro 7.2 Portfolio Sketch 7.3 Jumbotron 7.4 Nav Bar 7.5 Panels 7.6 Challenge 5 7.7 Portfolio Outre Module: 08 8.1 Hosting 8.2 Bluehost 8.3 Uploading 8.4 Tips 8.5 Hosting Outro Course 06: WebGL 2D/3D Programming and Graphics Rendering Section 01: Introduction Section 02: Drawing Objects Section 03: Colours and Textures Section 04: Moving & Transforming Objects Section 05: Movement & Camera Section 06: Lighting & Shading Course 07: Python for Data Analysis Welcome, Course Introduction & overview, and Environment set-up Python Essentials Python for Data Analysis using NumPy Python for Data Analysis using Pandas Python for Data Visualization using matplotlib Python for Data Visualization using Seaborn Python for Data Visualization using pandas Python for interactive & geographical plotting using Plotly and Cufflinks Capstone Project - Python for Data Analysis & Visualization Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Python for Machine Learning - scikit-learn - Logistic Regression Model Python for Machine Learning - scikit-learn - K Nearest Neighbors Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Python for Machine Learning - scikit-learn - K Means Clustering Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Recommender Systems with Python - (Additional Topic) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Course 08: Network Security Level 2 Security and Risk Management Asset Security Security Engineering Communication and Network Security Identity and Access Management Security Assessment and Testing Security Operations Software Development Security Course 09: SQL Server for Beginners Introduction Setup Basic queries Security MSSQL an ddifferent drivers Files General Course 10: Functional Skills IT Section 1: Introduction Section 2: Information Technology Section 3: Components of IT Section 4: Hardware Section 5: Operating System Section 6: Application/Software Section 7: Networking Section 8: Security Section 9: Traffic Flow & Enterprise Level IT Components Section 10: Storage Section 11: Database Section 12: Virtualisation & Cloud Section 13: Management & Other IT Jobs Course 11: Level 2 Microsoft Office Essentials Excel 2016 Getting Started with Microsoft Office Excel 2016 Performing Calculations Modifying a Worksheet Formatting a Worksheet Printing Workbooks Managing Workbooks Word 2016 Getting Started with Word Formatting Text and Paragraphs Working More Efficiently Managing Lists Adding Tables Inserting Graphic Objects Controlling Page Appearance Preparing to Publish a Document Workbooks - Microsoft Word 2016 (Beginner) PowerPoint 2016 PowerPoint Interface Presentation Basics Formatting Inserting Options Working with Objects Table Charts Review and Presentatin Access 2016 Introduction to Access Modify Data Working with Queries Access Forms Working with Reports CPD 135 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Web Application Penetration Testing & Security bundle. Persons with similar professions can also refresh or strengthen their skills by enrolling in this course. Students can take this course to gather professional knowledge besides their study or for the future. Requirements Our Web Application Penetration Testing & Security 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 expertise will increase the value in your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included