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Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) 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 Building Recommendation Systems with Python (TTAI2360) 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.

Kickstart your career with our Complete Python from Scratch: Start your career in Python 3+ course. Python is an all-purpose language with one of the biggest and abundant library features. It is used for a wide range of purposes such as web development, scripting, testing, app development, and data science. So it's one of the most sought after skills by employers. The Complete Python from Scratch: Start your career in Python 3+ course is designed to give you a complete understanding of the programming language right from setup to advanced level applications.The experience will provide you with the chance to work in a variety of sectors including web development, machine learning, data security, analytics and so much more. It will prepare you with sound theoretical and practical knowledge of Python programming that will prepare you to work with evidence-based strategies. If you are keen to equip yourself with knowledge of programming with Python and make a strategic career intervention, then choose our Complete Python from Scratch: Start your career in Python 3+ course. Upon completion of this CPD accredited course, you will be awarded a certificate of completion, as proof of your expertise in this field, and you can show off your certificate in your LinkedIn profile and in your resume to impress employers and boost your career. Our Complete Python from Scratch: Start your career in Python 3+ course is packed with 14 modules, with a total of 18 hours of learning materials. You will be able to study this course at your own pace, from anywhere and at any time. Enrol today and upgrade your knowledge on Python programming to lead a more prosperous life.

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents, and interests with our special Big Data Analytics with PySpark Power BI and MongoDB Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides the professional training that employers are looking for in today's workplaces. The Big Data Analytics with PySpark Power BI and MongoDB Course is one of the most prestigious training offered at Skillwise and is highly valued by employers for good reason. This Big Data Analytics with PySpark Power BI and MongoDB Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Big Data Analytics with PySpark Power BI and MongoDB Course, like every one of Skillwise's courses, is meticulously developed and well-researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At Skillwise, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from Skillwise, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Big Data Analytics with PySpark Power BI and MongoDB? Unlimited access to the course forever Digital Certificate, Transcript, and student ID are all included in the price Absolutely no hidden fees Directly receive CPD Quality Standard-accredited qualifications after course completion Receive one-to-one assistance every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Big Data Analytics with PySpark Power BI and MongoDB there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Who is this course for? This Big Data Analytics with PySpark Power BI and MongoDB course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skills. Prerequisites This Big Data Analytics with PySpark Power BI and MongoDB does not require you to have any prior qualifications or experience. You can just enroll and start learning. This Big Data Analytics with PySpark Power BI and MongoDB was made by professionals and it is compatible with all PCs, Macs, 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. Career path As this course comes with multiple courses included as a bonus, you will be able to pursue multiple occupations. This Big Data Analytics with PySpark Power BI and MongoDB is a great way for you to gain multiple skills from the comfort of your home.   Section 01: Introduction Introduction 00:10:00 Section 02: Setup and Installations Python Installation 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 Section 03: Data Processing with PySpark and MongoDB 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 Section 04: Machine Learning with PySpark and MLlib Data Pre-processing 00:19:00 Building the Predictive Model 00:12:00 Creating the Prediction Dataset 00:08:00 Section 05: Creating the Data Pipeline Scripts Installing Visual Studio Code 00:03:00 Creating the PySpark ETL Script 00:22:00 Creating the Machine Learning Script 00:24:00 Section 06: Tableau Data Visualization Installing Tableau 00:03:00 Installing MongoDB ODBC Drivers 00:03:00 Creating a System DSN for MongoDB 00:04:00 Loading the Data Sources 00:04:00 Creating a Geo Map 00:11:00 Creating a Bar Chart 00:03:00 Creating a Magnitude Chart 00:07:00 Creating a Table Plot 00:06:00 Creating a Dashboard 00:07:00 Source Code Source Code and Notebook

48-Hour Knowledge Knockdown! Prices Reduced Like Never Before! Unlock the power of Data Analyst (Data Analytics) with our cutting-edge Data Analyst (Data Analytics) course and transform raw information into strategic insights of Data Analyst (Data Analytics) that drive success. Get Free 1 QLS Endorsed Course with Certificate & 10 Additional CPD Accredited Courses In A Single Payment. This Data Analyst (Data Analytics) Bundle Package includes: Course 01: Diploma in Data Analysis at QLS Level 5 10 Additional CPD Accredited Premium Courses related to Data Analyst (Data Analytics) - Course 01: Data Analytics with Tableau Course 02: Data Science & Machine Learning with R Course 03: Excel Pivot table for Data analytics Course 04: JavaScript Functions for Data Analyst Course 05: Data analytics with Excel Course 06: Mastering SQL Programming for Data Analyst Course 07: Google Data Studio Course 08: Business Intelligence and Data Mining for Data Analyst Course 09: GDPR Training Course 10: Learn Programming with Python Learning outcome of this Data Analyst (Data Analytics) Bundle: Apply data analyst techniques to modify worksheets effectively. Utilise data analyst strategies for working with lists. Demonstrate proficiency in analyzing data as a data analyst. Visualize data using charts as a data analyst. Employ PivotTables and Pivot Charts for complex Data Analyst Manage multiple worksheets and workbooks efficiently as a data analyst. Use lookup functions and formula auditing for accurate Data Analyst Why Prefer This Data Analyst (Data Analytics) Bundle? FREE certificate on Data Analyst (Data Analytics)accredited by CPDQS Get instant access to this Data Analyst (Data Analytics) course. Learn Data Analyst (Data Analytics) from anywhere in the world Data Analyst (Data Analytics) is affordable and simple to understand Data Analyst (Data Analytics) is an entirely online, interactive lesson with voiceover audio Lifetime access to the Data Analyst (Data Analytics) bundle materials Data Analyst (Data Analytics) comes with 24/7 tutor support Free assessments available with Data Analyst (Data Analytics) Get a free student ID card! with Data Analyst (Data Analytics) Assessment Process of Data Analyst (Data Analytics) Course: You have to complete the assignment questions given at the end of the Data Analyst (Data Analytics) course and score a minimum of 60% to pass each exam, after that you can claim your certificate CPD 100 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is for whoever wishes to gain a better understanding of Data Analyst (Data Analytics) Requirements You will not need any prior background or expertise to take this Data Analyst (Data Analytics) Career path Data Analyst Retail Data Analyst Statistical Data Analyst Certificates CPD Accredited e-Certificate Digital certificate - Included Diploma in Data Analysis at QLS Level 5 Hard copy certificate - Included

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is as follows: IT Solution Architects Network Security Architects Networking Admin and Operations Networking Field Engineers In this workshop you will learn why we are implementing Assurance, and what does looks like and key features. We will also discuss the Cisco DNA center appliance and workflow and tasks associated with an implementation. Module 1: Introduction to Cisco DNA Center Assurance Introduction to DNA Center System Architecture Key Features and Use Cases Introduction to Cisco ISE and DNAC-ISE integration Module 2: Design Network design options Sites Creating Enterprise and Sites Hierarchy Configuring General Network Settings Loading maps into the GUI IP Address Management Software Image Management ? Lab on Day 5 Network Device Profiles AAA SNMP Syslog IP address pools Creating Enterprise and Guest SSIDs ? Lab on Day 2 Creating the wireless RF Profile Cresting the Guest Portal for the Guest SSIDs Network profiles ? Lab on Day 2 Authentication templates Module 3: Discovery and Provision Device Discovery and Protocols Devices Onboarding Assigning Devices to a site Provisioning device with profiles Plug and Play Templates Templates for Day-0 Templates for Day-N operations Module 4: Monitoring Device, Client, and Application Health DNAC Telemetry Monitoring Network Device Health and Performance Monitoring Wired and Wireless Client Health and Performance Monitoring Application Health and Performance Module 5: Application Visibility and DNAC Integration with Umbrella Monitoring Application Visibility in DNA Center Umbrella Introduction DNA Center Umbrella Integration and Use Cases Module 6: Troubleshooting Issues, Observing Insights and Trends Detect Issues, Insights, and Trends in the Network DNA Center Integration with other tools for Monitoring and Management Module 7: Troubleshooting using Cisco DNA Center Assurance Tools DNAC Assurance Troubleshooting Tools Using Sensor Tests Using Intelligent Capture Spectrum Analysis Module 8: DNAC and Thousand Eyes Introduction to ThousandEyes ThousandEyes Use Cases DNA Center and ThousandEyes Integration Module 9: AI Analytics and Machine Learning in DNA Center Overview of AI Analytics and ML (Machine Learning) DNA Center AI and ML Use Cases Module 10: DNA Center Maintenance DNA Center Reports DNA Center Backup and Restore

SQL Azure is Microsoft's cloud database service. Based on SQL Server database technology and built on Microsoft's Windows Azure cloud computing platform, SQL Azure enables organizations to store relational data in the cloud and quickly scale the size of their databases up or down as business needs change.  This Azure - SQL focuses primarily on Azure SQL Database as a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software. Learn how to deploy relational and non-relational databases in the cloud and explore the breadth of Azure's data services, from a single database instance to a massive scale data warehouse for working with Big data. You'll gain an understanding of how to configure firewall rules, manage log-ins and users, as well as roles and permissions, perform a database restore, and generally secure an Azure SQL database. Finally, you'll be introduced to Azure SQL Data Warehouse, a fully managed and scalable cloud service, that is compatible with other Azure offerings, such as Machine Learning and Data Factory, as well as existing SQL Server tools. What Will I Learn? Overview and provision Azure SQL Connect to Azure SQL DB and Migrate DB to Azure Work with SQL security and metrics Configure SQL DB auditing Copy and export a database Use DB Self-Service Restore and SQL DB Geo-Replication Who is the target audience? Students wanting an understanding of Azure SQL and to build their skills. Requirements Basic understanding of Azure and SQL concepts Introduction Introduction FREE 00:02:00 Azure SQL Azure SQL 00:02:00 Provisioning Azure SQL 00:06:00 Connecting to Azure SQL DB 00:08:00 Migrating to Azure DB 00:06:00 Understanding SQL Security 00:03:00 Understanding SQL DB Metrics and Auditing 00:05:00 Backing Up and Protecting your Database 00:05:00 Using SQL DB Geo-Replication 00:03:00 Conclusion Course Recap 00:02:00 Course Certification

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Individuals planning to deploy applications and create application environments on Google Cloud Platform Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs. Overview This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing,storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences This 1-day instructor led course introduces Azure professionals to the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for Azure system administrators, Solution Architects and SysOps Administrators familiar with Azure features and setup; and want to gain experience configuring Google Cloud products immediately. With presentations, demos, and hands-on labs, participants get details of similarities, differences, and initial how-tos quickly. Introducing Google Cloud Explain the advantages of Google Cloud. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Identify the purpose of projects on Google Cloud. Understand how Azure's resource hierarchy differs from Google Cloud's Understand the purpose of and use cases for Identity and Access Management. Understand how Azure AD differs from Google Cloud IAM. List the methods of interacting with Google Cloud. Launch a solution using Cloud Marketplace. Virtual Machines in the Cloud Identify the purpose and use cases for Google Compute Engine Understand the basics of networking in Google Cloud. Understand how Azure VPC differs from Google VPC. Understand the similarities and differences between Azure VM and Google Compute Engine. Understand how typical approaches to load-balancing in Google Cloud differ from those in Azure. Deploy applications using Google Compute Engine Storage in the Cloud Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore. Understand how Azure Blob compares to Cloud Storage. Compare Google Cloud?s managed database services with Azure SQL. Learn how to choose among the various storage options on Google Cloud. Load data from Cloud Storage into BigQuery Containers in the Cloud Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Understand how Azure Kubernetes Service differs from from Google Kubernetes Engine. Provision a Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl Applications in the Cloud Understand the purpose of and use cases for Google App Engine. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand how App Engine differs from Azure App Service. Understand the purpose of and use cases for Google Cloud Endpoints. Developing, Deploying and Monitoring in the Cloud Understand options for software developers to host their source code. Understand the purpose of template-based creation and management of resources. Understand how Google Cloud Deployment Manager differs from Azure Resource Manager. Understand the purpose of integrated monitoring, alerting, and debugging Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics. Create a Deployment Manager deployment. Update a Deployment Manager deployment. View the load on a VM instance using Google Monitoring. Big Data and Machine Learning in the Cloud Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Understand how Google Cloud BigQuery differs from Azure Data Lake. Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus. Understand how Google Cloud?s machine-learning APIs differ from Azure's. Load data into BigQuery from Cloud Storage. Perform queries using BigQuery to gain insight into data Summary and Review Review the products that make up Google Cloud and remember how to choose among them Understand next steps for training and certification Understand, at a high level, the process of migrating from Azure to Google Cloud.

Are you interested in pursuing a career in the Computer Science Advanced Diploma industry or learning more about it? If yes, then you have come to the right place. Our comprehensive courses on Computer Science Advanced Diploma will assist you in producing the best possible outcome by learning the Computer Science Advanced Diploma skills. The Computer Science Advanced Diploma bundle is for those who want to be successful. In the Computer Science Advanced Diploma bundle, you will learn the essential knowledge needed to become well versed in Computer Science Advanced Diploma. Why would you choose the Computer Science Advanced Diploma course from Compliance Central: Lifetime access to Computer Science Advanced Diploma courses materials Full tutor support is available from Monday to Friday with the Computer Science Advanced Diploma course Learn Computer Science Advanced Diploma skills at your own pace from the comfort of your home Gain a complete understanding of Computer Science Advanced Diploma course Accessible, informative Computer Science Advanced Diploma learning modules designed by expert instructors Get 24/7 help or advice from our email and live chat teams with the Computer Science Advanced Diploma bundle Study Computer Science Advanced Diploma in your own time through your computer, tablet or mobile device Our Computer Science Advanced Diploma bundle starts with the basics of Computer Science Advanced Diploma and gradually progresses towards advanced topics. Therefore, each lesson of this Computer Science Advanced Diploma is intuitive and easy to understand. Courses in this Computer Science Advanced Diploma Bundle: Course 01: Computer Science with Python Course 02: Diploma in Front-End Web Development (HTML, CSS, & Bootstrap) Course 03: It: Ethical Hacking, IT Security and IT Cyber Attacking Course 04: Data Science and Visualisation with Machine Learning Course 05: Info Graphics Web Design - Affinity Designer Training Course 06: Website Hacking From Scratch Course 07: Web Application Penetration Testing Course Course 08: Excel Add-in with C# VSTO and Web Course 09: C++ Programming for Absolute Beginnerss Course 10: Computer Vision: C++ and OpenCV with GPU support Course 11: Learning Effective UX Designs Course 12: C++ Coding Masterclass CPD 120 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Computer Science Advanced Diploma bundle helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Computer Science Advanced Diploma. Requirements To enrol in this Computer Science Advanced Diploma course, all you need is a basic understanding of the English Language and an internet connection. Career path The Computer Science Advanced Diploma bundle will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Computer Science Advanced Diploma. Certificates 12 CPD Accredited PDF Certificate Digital certificate - Included Each CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD accredited hard copy certificates are available for £10.79 each Delivery Charge for Each Hard Copy Certificates: Inside the UK: Free Outside of the UK: £9.99 each