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Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

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Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Gain the skills and credentials to kickstart a successful career in the technology industry and learn from the

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Overview ChatGPT for Marketing and Productivity with AI Tools Course is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this ChatGPT for Marketing and Productivity with AI Tools Course and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 05 Hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification CPD Certification from The Teachers Training After you have successfully completed your assignment, you will be qualified to apply for a CPD Certification from The Teachers Training. The PDF certificate can be downloaded after you have completed your course. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Section 01: The AI Marketing Playbook Unit 01: Start an Account with ChatGPT 00:02:00 Unit 02: What the Company OpenAI Say About Itself 00:02:00 Unit 03: What OpenAI Say About The Limitations of the Chatbot 00:02:00 Unit 04: Chatbot Prompt Examples Given By Open AI 00:02:00 Unit 05: Will Chat GPT Be a Paid Application 00:01:00 Unit 06: Chat GPT Idea Generation 00:02:00 Unit 07: Chat GPT - Idea Qualification and Accuracy 00:03:00 Unit 08: ChatGPT - Accuracy and Citations 00:02:00 Unit 09: Chat GPT - Creating HTML Instances 00:01:00 Unit 10: Chat GPT - How to Solve Specific Business Problems 00:02:00 Unit 11: Chat GPT - Statistical Verification of Information 00:01:00 Unit 12: Chat GPT - Rewrite Content for Different Contexts 00:02:00 Unit 13: ChatGPT - Content Checked With AI 00:02:00 Unit 14: ChatGPT - Simplifying Information 00:01:00 Unit 15: ChatGPT - How to Ask the Chatbot about Context 00:01:00 Unit 16: ChatGPT - How to Cross-Post Queries 00:01:00 Unit 17: ChatGPT - How to Narrow Down the Context of Your Query 00:02:00 Unit 18: ChatGPT - How to Solve a Business Process 00:02:00 Unit 19: ChatGPT - Developing a Methodology From Experts 00:01:00 Unit 20: The Future of ChatGPT 00:01:00 Section 02: How to Use ChatGPT and AI for Marketing Unit 01: Autonous AI Agents 00:01:00 Unit 02: Connecting to Open AI 00:01:00 Unit 03: Getting an OpenAI Key 00:01:00 Unit 04: Agent GPT - Autonomous AI 00:02:00 Unit 05: GoalGPT - Autonomous Agents 00:01:00 Unit 06: Cognosis - Autonomous AI 00:02:00 Unit 07: Aomni - Autonomous Agent 00:01:00 Unit 08: Durable - Build a Website with AI 00:01:00 Unit 09: Eightify Summaries 00:02:00 Unit 10: Genei - Do Higher Quality Research with AI 00:01:00 Unit 11: Ellicit - Do Higher Quality Research with AI 00:01:00 Unit 12: Inciteful - Do Higher Quality Research with AI 00:02:00 Unit 13: SciteAI Determine the Credibility of Your Research 00:01:00 Unit 14: Eleven Labs - Voice Cloning 00:02:00 Unit 15: AgentGPT - Wrap Up and Return 00:01:00 Unit 16: Cognosys - Wrap Up and Return 00:01:00 Unit 17: Aomni - Wrap Up and Return 00:01:00 Unit 18: Goal GPT - Wrap Up and Return 00:01:00 Unit 19: Uploading Research Reports to Summarization Applications 00:01:00 Unit 20: Perspective on The Future of AI 00:01:00 Section 03: Productivity with AI Tools Unit 01: Meta Search Sites 00:02:00 Unit 02: SMMRY for Summarzing 00:01:00 Unit 03: ChatGPT Plugins Waitlist 00:01:00 Unit 04: Using Microsoft Bing Search 00:02:00 Unit 05: Using Google Bard 00:01:00 Unit 06: Microsoft Word Speech To Text 00:01:00 Unit 07: Transcribe Audio in Microsoft Word 00:02:00 Unit 08: Speechify 00:02:00 Unit 09: Exact Image Creation 00:01:00 Unit 10: AI Design Tools 00:02:00 Unit 11: Learn How to Prompt 00:01:00 Unit 12: Content Improvement 00:01:00 Unit 13: Idea Generation 00:01:00 Unit 14: Audio Enhancement with Adobe 00:02:00 Unit 15: Clean up Audio With Cleaanvoice 00:01:00 Unit 16: Notion-AI 00:01:00 Unit 17: Pictory 00:01:00 Unit 18: Lex 00:01:00 Unit 19: ChatPDF 00:01:00 Unit 20: Conclusion and the Future of Generatie AI - Searchie 00:01:00

Artificial neural networks (ANNs) are the most powerful machine learning algorithms available today. They are capable of learning complex relationships in data, and they have been used to achieve state-of-the-art results in a wide variety of fields, including image recognition, natural language processing, and speech recognition. The Future of Machine Learning is Here! This Project on Deep Learning - Artificial Neural Network course will teach you how to build and train ANNs from scratch. You will learn about the different components of an ANN, such as the input layer, hidden layers, and output layer. You will also learn about the different activation functions that can be used in ANNs, and you will see how to optimise ANNs for different tasks. In addition to the theoretical concepts, you will also get experience with ANNs. You will work on a project where you will build an ANN to classify images. You will use the TensorFlow library to build your ANN, and you will see how to train your ANN on a dataset of images. By the end of this Project on Deep Learning - Artificial Neural Network course, you will have a deep understanding of ANNs and how to use them. You will be able to build your own ANNs to solve a variety of problems. You will also be able to use the TensorFlow library to build and train ANNs. So what are you waiting for? Enrol in this course today and start learning about the future of machine learning!   Learning Outcomes: Through this comprehensive course, you should be able to: Understand the fundamental concepts of deep learning and artificial neural networks. Install and configure an artificial neural network framework. Preprocess and structure data for optimal model performance. Encode data effectively for neural network training and predictions. Build and deploy artificial neural networks for real-world applications. Address data imbalance challenges and optimise model accuracy.   Who is this course for? This Project on Deep Learning - Artificial Neural Network course is ideal for: Data scientists and machine learning practitioners seeking to expand their knowledge. Software engineers interested in leveraging deep learning techniques. Students pursuing a career in artificial intelligence and machine learning. Professionals looking to enhance their skills in neural network development. Individuals with a passion for exploring advanced machine learning techniques.   Career Path  Our course will prepare you for a range of careers, including: Deep Learning Engineer: £40,000 - £100,000 per year. Machine Learning Researcher: £45,000 - £120,000 per year. Data Scientist: £50,000 - £110,000 per year. Artificial Intelligence Specialist: £55,000 - £130,000 per year. Software Engineer (specialising in AI): £45,000 - £100,000 per year. Research Scientist (Machine Learning): £50,000 - £120,000 per year. AI Consultant: £60,000 - £150,000 per year. Certification After studying the course materials of the Project on Deep Learning - Artificial Neural Network (ANNs) 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 £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Prerequisites This Project on Deep Learning - Artificial Neural Network (ANNs) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Project on Deep Learning - Artificial Neural Network (ANNs) 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.   Course Curriculum Section 01: Introduction Introduction of Project 00:03:00 Section 02: ANN Installation Setup Environment for ANN 00:11:00 ANN Installation 00:09:00 Section 03: Data Preprocessing Import Libraries and Data Preprocessing 00:11:00 Data Preprocessing 00:07:00 Data Preprocessing Continue 00:10:00 Section 04: Data Encoding Data Exploration 00:10:00 Encoding 00:07:00 Encoding Continue 00:06:00 Preparation of Dataset for Training 00:04:00 Section 05: Steps to Build ANN Steps to Build ANN Part 1 00:06:00 Steps to Build ANN Part 2 00:06:00 Steps to Build ANN Part 3 00:06:00 Steps to Build ANN Part 4 00:09:00 Section 06: Predictions and Imbalance-Learn Predictions 00:11:00 Predictions Continue 00:08:00 Resampling Data with Imbalance-Learn 00:09:00 Resampling Data with Imbalance-Learn Continue 00:08:00