Curriculum Overview
Get the full DECT curriculum at a glance — download the overview documents or browse every course.
Get the full DECT curriculum at a glance — download the overview documents or browse every course.
This professional animation foundation course is designed for all students who want to pursue a career in animation, whether 2D or 3D animation fields. In 12 weeks, you will build a solid foundation of animation principles by learning from the experiences of the best animators in the industry. The course will first trace the history of animation, then elaborate on the animation process, and finally cover animation production using 2D and 3D tools. The course will also focus on character animations, such as posing, timing, and actions.
This course aims to provide students with an in-depth understanding of artificial intelligence (AI) image generation techniques and their application in creative projects to create visually appealing images. The course will provide students with a detailed overview of the AI image generation process, including how to select and construct key terms to control character feature generation for commercially-applicable concept artworks. The instructor will also show students how to use AI tools to translate their creative ideas and emotions into visuals that can be used in concept design, split-screening, comic drawing, game and animation creation to achieve ideal, cost-effective, and smooth graphics. ----------------------------------------------- Course Structure: 1. Introduction to basic AI techniques: introduction to the basic background, historical process and principles of AI image generation techniques; explain how to use AI systems and how to make judgments about different application contexts 2. Image representation: learn about graphic and data representation, and how aspects of color, light, contrast and color differences relate to other color channels in images 3. AI image generation: learn how to use popular AI image generation tools to generate high quality images; make good use of official websites for filtering searches and use shared open databases; connect with developers of movies and games for fast, low-cost and diverse character settings 4. AI creation: Use AI to generate various music styles, and use what you have learned to start producing AI-generated comics and games
AI music generation is the process of generating music using artificial intelligence. By analyzing music data and patterns and using machine learning algorithms, different types of music can be generated, including pop, jazz, classical, and more. This course starts with an overview of music generation techniques and is centered around mastering different kinds of music generation techniques. Students will also be able to learn basic music theory such as music structure, genre, chords, melody, rhythm, and music format. The course is suitable for beginners. By completing practical projects, students can better understand the principles and practical applications of AI music generation, and use AI to create different music compositions to improve the efficiency and creativity of music creation.
In this course, students will learn about Natural Language Processing (NLP) techniques and common language models such as RNN, LSTM, and Transformer. They will learn content generation skills including how to generate text for Q&A and how to improve the accuracy of Q&A using the ChatGPT tool as a learning model. The course will also delve into the future of chat AI and Q&A systems, and their possible applications in different fields.
This course will teach you how to use Artificial Intelligence (AI) to generate videos. The instructor will introduce the basic concepts of animation: frame rate, storyboard, special effects, etc. The instructor will also introduce the current application of AI in the animation industry, such as how the industry uses the latest AI technology to assist in storyboarding, motion capture, special effects, adding subtitles and background music. By the end of the course, students will use their knowledge of AI animation production processes and techniques to generate their own short animation.
This course will introduce students to the use of AI-assisted tools in CG animation and graphic design. Students will learn how to integrate AI tools into their creative workflows, and explore how AI can be used to enhance various aspects of production, such as character design, 3D modeling, animation, and special effects. By the end of the course, students will have developed a solid understanding of how AI can be leveraged in CG animation and graphic design, and will have created a final project that showcases their skills and knowledge. --------------------------------------- Career Preparation: The course is designed to prepare students for careers in the CG, animation and graphic design industries. The skills and knowledge gained from the course will provide students with a competitive advantage when seeking employment in these fields. The ability to use AI-assisted techniques in CG, animation and graphic design is in high demand, and this course will enable students to meet this demand and excel in their careers.
The objective of this 800-hour curriculum is to equip students with the necessary knowledge and skills to create CG feature animations using open source AI and design tools. The curriculum will cover all the aspects of CG animation, from script writing to final rendering, and students will be expected to develop a strong foundation in all the relevant technical areas. Through this course, students will learn to use AI tools to speed up the animation production process and create realistic and stunning animations. ----------------------------- Introducing AI to traditional workflows With the increasing demand for high-quality CG feature animations, there is a need for artists and animators who are skilled in the use of open source AI and design tools. This course aims to provide students with the knowledge and skills necessary to create CG feature animations using these tools, and to explore the potential of AI and other emerging technologies in the field. By working collaboratively in a team, students will also develop important interpersonal skills that are essential for success in the creative industries. Course curriculum: The 800-hour CG feature animation course will be delivered over a period of 20 weeks, with classes held for 40 hours each week. The following is a breakdown of the time table for the course: Weeks 1-2: Introduction to CG Feature Animation During the first two weeks of the course, students will be introduced to the basic concepts and principles of CG feature animation. This will include an overview of the course, an introduction to the software and tools that will be used throughout the program, and an overview of the CG feature animation production pipeline. Students will also begin working on their first project, which will involve creating a simple 3D model using Blender AI. Weeks 3-4: Character Design and Modeling In weeks 3 and 4, students will be introduced to the principles of character design and modeling. This will include an overview of the design process, character anatomy, and the basics of 3D modeling. Students will also be introduced to the Midjourney software tool, which will be used for character design. During this section, students will work on designing and modeling their own original characters. Weeks 5-6: Environment Design and World Building During weeks 5 and 6, students will learn about environment design and world building. This will include an introduction to mood board creation, environmental storytelling, and the creation of assets for use in environments. Students will also begin to work on designing and building their own environments using Blender AI. Weeks 7-8: Special Effects and Simulation In weeks 7 and 8, students will learn about special effects and simulation. This will include an introduction to Stable Diffusion software tool, which will be used for creating special effects. Students will work on adding special effects to their characters and environments. Weeks 9-10: Crowd Scene and Motion Capture In weeks 9 and 10, students will learn about crowd scenes and motion capture. This will include an introduction to the Point-E and PifuHD software tools, which will be used for motion capture and facial expression transfer. Students will work on adding motion capture to their characters and creating a crowd scene. Weeks 11-12: Sound Design and Video Compositing In weeks 11 and 12, students will learn about sound design and video compositing. This will include an introduction to sound design principles and the use of sound in animation, as well as an introduction to the Kdenlive software tool, which will be used for video compositing and editing. Students will work on creating their own sound design and integrating it into their final project. Weeks 13-14: Texture, Lighting, and Rendering In weeks 13 and 14, students will learn about texture, lighting, and rendering. This will include an introduction to texture creation and editing using Krystal Office+(GIMP, Krita, and Inkscape,), as well as an introduction to lighting and rendering in Blender AI. Students will work on adding textures, lighting, and rendering to their final project. Weeks 15-16: Final Graduation Project During the final two weeks of the course, students will work on their final graduation project. This will involve using all the skills and tools they have learned throughout the program to create a high-quality CG feature animation. Students will be required to submit a completed project that meets certain quality standards, which will be outlined in the project guidelines. Throughout the course, students will have access to additional resources and materials, such as video tutorials and online forums, to support their learning and development. The course will also include regular assessments and feedback to help students track their progress and identify areas where they need to improve.
The objective of this curriculum is to equip students with the necessary skills and knowledge to create immersive experiences in the Metaverse using various AI tools. The course covers a broad range of topics including Virtual Reality (VR), Extended Reality (XR), Web3, Non-Fungible Tokens (NFT), Blockchain, Decentralized Autonomous Organizations (DAO), and various AI tools. ----------------------------------------------- The Importance of AI Tools to Metaverse Content Creation The Metaverse is a rapidly evolving technology that promises to create immersive and engaging experiences for users. With the rise of NFTs and blockchain technology, the Metaverse is becoming a new platform for content creation and distribution. As the demand for immersive content grows, content creators need the assistance of various AI tools to efficiently create high-quality Metaverse experiences. Course Outline: Module 1 : Introduction to the Metaverse and Virtual World Design Principles • Course objectives and outcomes • Overview of the Metaverse and its potential • Introduction to virtual world design principles • Creating a virtual space in Blender Module 2: VR and XR Design • Introduction to VR and XR design • Designing for VR and XR interfaces • Creating 3D models in Blender • Creating textures in GIMP and Krita Module 3: MR Design and Development • Introduction to MR design • Creating MR experiences using Unity and Godot • Implementing AR elements in a virtual world • Introduction to blockchain and its use in the Metaverse Module 4: UI/UX Design • Introduction to UI/UX design principles • Designing for user experience in the Metaverse • Introduction to Inkscape and Kdenlive • Designing and prototyping UI/UX interfaces Module 5: NFTs and Web3 • Introduction to NFTs and their use in the Metaverse • Introduction to Web3 and its use in the Metaverse • Creating NFTs using Get3D and PifuHD • Integrating NFTs into a virtual world using smart contracts and DAOs Module 6: AI for World Building • Introduction to AI-powered world building • Using Blender AI for generative modeling • Using Midjourney for texture synthesis • Using Stable Diffusion for image manipulation Module 7: Video Editing and Machinima • Introduction to video editing in the Metaverse • Using Black Magic DaVinci and Natron for video editing • Introduction to Omniverse Machinima • Creating a short film using Machinima techniques Module 8: Creating Personalized Avatars • Introduction to avatar design and customization • Using Luma AI and Point-E for facial recognition and avatar generation • Using Dream Fusion and Godot for avatar animation and integration Module 9: Building Virtual Real Estate • Introduction to building virtual real estate • Using UPBGE for real-time rendering • Creating a virtual store and marketplace using Metamask • Implementing blockchain-based ownership and exchange of virtual real estate Module 10: Final Project and Presentation • Working collaboratively in teams to create a virtual world in the Metaverse • Incorporating various use cases of the Metaverse • Demonstrating knowledge and skills acquired throughout the course • Final project presentation and evaluation
This course aims to introduce 3rd-grade students to the fascinating world of artificial intelligence in an age-appropriate, engaging, and enjoyable manner. By familiarizing students with AI tools and concepts, they can better understand the increasingly digital world around them and develop essential skills for the future. Through hands-on activities, games, creative exercises, and a fun final project, students will be encouraged to think critically and creatively about AI and its potential while fostering collaboration and cultivating problem-solving skills. ------------------------------------------ Fun and Simple Final Project: "AI Superheroes" For the final project, students will work in teams to create a short comic strip featuring AI-powered superheroes. They will use ChatGPT to help generate ideas, storylines, and character backgrounds, incorporating their own creativity and imagination. They will use Midjourney to generate graphics to enrich their final projects. Students can draw their own illustrations or use AI-powered tools like NVIDIA Canvas for creating scenes. The comic strip should have 3-5 panels and include a beginning, middle, and end. Students will present their comic strips to the class and explain how they incorporated AI tools in their project. Course Outline: Session 1: Introduction to Artificial Intelligence • What is Artificial Intelligence? • Examples of AI in everyday life • Simple explanation of how AI works Session 2: ChatGPT - A Friendly AI Helper • Introduction to ChatGPT • A simple demonstration of ChatGPT • Hands-on activity: Asking ChatGPT questions Session 3: Midjourney - Plan Your AI Journey • Introduction to Midjourney • A simple demonstration of Midjourney's graphic generating prompt • Hands-on activity: Planning a dream vacation using Midjourney Session 4: AI music • Introduction to AI Music tools • A simple demonstration of AI music tools • Hands-on activity: Make your own music Session 5: AI in Our Lives • AI voice assistants: Siri and Alexa ◦ What they do and how they work ◦ Hands-on activity: Asking Siri or Alexa questions • AI in games and toys • AI in movies and cartoons • AI helpers around us Session 6: Jobs and AI • Simple explanation of how AI can change jobs in the future • Exploring future jobs involving AI • Group discussion: How can AI help us in our future jobs? Session 7: Being Responsible with AI • Understanding the importance of using AI responsibly • The importance of fairness and kindness in AI • Group discussion: How can we make sure AI is used for good? Session 8: AI Games and Activities • Quick, Draw! • AI Dungeon (guided and moderated) • Rock, Paper, Scissors with AI • Teachable Machine Session 9: AI-Powered Art with NVIDIA Canvas • Introduction to NVIDIA Canvas • Demonstration of how NVIDIA Canvas works • Hands-on activity: Creating simple scenes and landscapes with NVIDIA Canvas • Sharing and discussing students' creations Session 10: Introduction to the Final Project - "AI Superheroes" • Explaining the final project concept and guidelines • Forming teams and brainstorming ideas • Introduction to AI tools for the project, such as ChatGPT and NVIDIA Canvas Session 11: Working on the Final Project • Teams work on their AI superhero comic strips using AI tools • Teacher supervision and guidance as needed • Finalizing comic strips and preparing for presentations Session 12: Final Project Presentations and Reflection • Studelnts present their AI superhero comic strips to the class • Group discussion on the projects and the overall learning experience • Reflecting on the fun and exciting things AI can do • Course summary and closing thoughts
This course aims to provide students with an opportunity to explore the intersection of AI and computer graphics in animation production. Through hands-on experience and project-based learning, students will develop a strong foundation in AI-assisted CG animation, equipping them with valuable skills for their future. -------------------------------------------- Course Structure: The course is designed to be accessible and engaging for kids, using language that is easy to understand. Each week's session will be divided into three parts: 1. Theory: Students will learn the concepts and principles behind the tools and techniques they will use. This portion will be delivered through simple explanations, videos, and demonstrations. 2. Hands-on Practice: Students will get hands-on experience using the tools and techniques they learned in the theory session. They will work on small exercises and mini-projects, applying their newly acquired knowledge. 3. Reflection and Feedback: At the end of each session, students will share their work, give and receive feedback, and reflect on their learning experience. This will help them grow and develop their skills further. Course Outline: Module 1: Introduction to AI Tools and CG Animation (4 hours) • Introduction to AI, computer graphics, and animation (1 hour) • Overview of AI tools used in CG animation production (1 hour) • Setting up software and tools (2 hours) Module 2: 3D Modeling with Blender 3D and Get3D (4 hours) • Introduction to Blender 3D and Get3D (1 hour) • Creating and editing basic 3D models (1.5 hours) • AI-assisted 3D modeling techniques (1.5 hours) Module 3: Art and Design with Inkscape and GIMP (4 hours) • Introduction to Inkscape and GIMP (1 hour) • Creating 2D assets for animation projects (1.5 hours) • AI-assisted art and design techniques (1.5 hours) Module 4: Animation with Leonardo AI (4 hours) • Introduction to Leonardo AI (1 hour) • Creating basic animations using AI (1.5 hours) • Advanced AI-assisted animation techniques (1.5 hours) Module 5: Video and Sound Editing with Shotcut (4 hours) • Introduction to Shotcut (1 hour) • Editing video and sound for animation projects (1.5 hours) • AI-assisted video and sound editing techniques (1.5 hours) Module 6: Storytelling and Scriptwriting with ChatGPT (4 hours) • Introduction to ChatGPT (1 hour) • AI-assisted storytelling and scriptwriting (1.5 hours) • Collaboration and brainstorming techniques (1.5 hours) Module 7: Project Management with Midjourney AI (4 hours) • Introduction to Midjourney AI (1 hour) • Planning and managing animation projects (1.5 hours) • AI-assisted project management techniques (1.5 hours) Module 8: Final Project and Presentation (4 hours) • Final project work (2 hours) • Project presentations and feedback (2 hours)
Vector databases are specialized databases designed to efficiently store, search, and retrieve high-dimensional vectors. They are particularly useful in applications where data points need to be compared based on similarity or proximity, such as machine learning (ML) and artificial intelligence (AI). This course aims to help students learn to design, implement, and manage vector databases for AI and ML applications, as well as perform efficient similarity search and high-dimensional data processing. The course uses Python, and will include training in Python programming as part of the syllabus for students who have less experience with the language. ---------------------------------- Common uses of vector databases: 1. Recommendation systems: Vector databases can be used to find similar items or users based on their feature vectors, enabling personalized recommendations. 2. Image search and computer vision: High-dimensional feature vectors can represent images, allowing vector databases to perform similarity search for image retrieval or object recognition tasks. 3. Natural language processing (NLP): Word embeddings and document vectors can be stored in a vector database for tasks like text similarity search, semantic analysis, and machine translation. 4. Anomaly detection: Vector databases can identify unusual data points or outliers by comparing their feature vectors to the rest of the data. 5. Clustering and classification: Vector databases can be used to perform clustering and classification tasks in unsupervised and supervised ML scenarios. Course Structure: Learning Python (40 hours): Week 1: Introduction to Python Programming (10 hours) · Python data types, variables, and operators (3 hours) · Control structures: conditionals, loops, and exception handling (4 hours) · Functions, modules, and libraries (3 hours) Week 2: Object-Oriented Programming in Python (10 hours) · Classes, objects, and inheritance (4 hours) · Encapsulation, polymorphism, and abstraction (4 hours) · Design patterns and best practices (2 hours) Week 3: Python Libraries for Data Manipulation and Visualization (10 hours) · NumPy for numerical computing (3 hours) · Pandas for data manipulation (4 hours) · Matplotlib for data visualization (3 hours) Week 4: Linear Algebra Concepts and Implementation in Python (10 hours) · Vectors, matrices, and operations (4 hours) · Linear transformations and eigenvalues/eigenvectors (3 hours) · Introduction to optimization (3 hours) Vector Database and Data Management (160 hours): Week 1: Introduction to Vector Databases and High-Dimensional Data (10 hours) · Understanding vector databases and their role in AI and ML (3 hours) · High-dimensional data representation and challenges (4 hours) · Introduction to distance metrics and similarity search (3 hours) Week 2: Indexing Techniques and Distance Metrics (10 hours) · Overview of indexing techniques for vector databases (4 hours) · k-d trees, ball trees, HNSW graphs, and LSH (4 hours) · Distance metrics: Euclidean distance, cosine similarity, and Manhattan distance (2 hours) Week 3-4: Hands-on Exercises with Indexing Techniques and Distance Metrics (20 hours) Week 5: · Introduction to Pinecone, Faiss, Annoy, and Elasticsearch with vector extensions (4 hours) · Hands-on exercises with each tool (4 hours) · Integration with TensorFlow and PyTorch for ML applications (2 hours) Week 6-7: Case Studies and Practical Exercises with Vector Database Tools (20 hours) Week 8: Scalability and Advanced Topics (10 hours) · Data partitioning, load balancing, and distributed indexing (3 hours) · Query processing and optimization techniques (4 hours) · Data storage and management strategies (2 hours) · Security, privacy, and monitoring in vector databases (1 hour) Week 9-10: Real-World Use Cases and Applications (20 hours) · Image search and computer vision (5 hours) · Natural language processing and text similarity (5 hours) · Recommendation systems (5 hours) · Anomaly detection and clustering (5 hours) Week 11-14: Final Project - Proposal, Design, and Implementation (40 hours) Week 15: Presentation and Evaluation of Final Projects (10 hours) Week 16: Course Review and Additional Resources for Continued Learning (10 hours) Week 17: Advanced Distance Metrics and Evaluation Techniques (10 hours) · Minkowski distance, Jaccard similarity, and other distance metrics (4 hours) · Techniques for evaluating similarity search quality (3 hours) · Benchmarking and performance analysis (3 hours) Week 18: Advanced Integration with AI and ML Frameworks (10 hours) · Using vector databases with reinforcement learning frameworks (4 hours) · Integration with other AI frameworks and libraries (3 hours) · Cross-framework compatibility and best practices (3 hours) Week 19: Emerging Trends and Cutting-Edge Research (10 hours) · Survey of recent advances in vector database research (4 hours) · Analysis of emerging trends in AI and ML that impact vector databases (3 hours) · Discussion of open research problems and potential future developments (3 hours) Week 20: Optimization and Performance Tuning (10 hours) · Techniques for optimizing vector database performance (4 hours) · Load testing and stress testing (3 hours) · Identifying and addressing performance bottlenecks (3 hours) Week 21: Data Privacy and Security in Vector Databases (10 hours) · Privacy-preserving similarity search techniques (4 hours) · Secure data storage and access control in vector databases (3 hours) · Regulations and compliance considerations (3 hours) Week 22: Building Custom Vector Database Solutions (10 hours) · Overview of open-source vector database projects (3 hours) · Designing and implementing a custom vector database solution (4 hours) · Contributing to open-source vector database projects (3 hours) Week 23: Industry Guest Lectures and Case Studies (10 hours) · Guest lectures from industry professionals on vector database applications (5 hours) · Analysis of real-world case studies in various industries (5 hours) Week 24: Course Reflection and Career Opportunities (10 hours) · Discussion of career paths and opportunities in the field of vector databases and high-dimensional data management (4 hours) · Review of course concepts and how they apply to real-world problems (3 hours) · Preparation for job interviews and portfolio development (3 hours)
The objective of this 800-hour curriculum is to equip students with the necessary knowledge and skills to create CG feature animations using open source AI and design tools. The curriculum will cover all the aspects of CG animation, from script writing to final rendering, and students will be expected to develop a strong foundation in all the relevant technical areas. Through this course, students will learn to use AI tools to speed up the animation production process and create realistic and stunning animations. ----------------------------------------- Need For Creative Talents: With the increasing demand for high-quality CG feature animations, there is a need for artists and animators who are skilled in the use of open source AI and design tools. This course aims to provide students with the knowledge and skills necessary to create CG feature animations using these tools, and to explore the potential of AI and other emerging technologies in the field. By working collaboratively in a team, students will also develop important interpersonal skills that are essential for success in the creative industries. Course Curriculum: Weeks 1-2: Introduction to CG Feature Animation During the first two weeks of the course, students will be introduced to the basic concepts and principles of CG feature animation. This will include an overview of the course, an introduction to the software and tools that will be used throughout the program, and an overview of the CG feature animation production pipeline. Students will also begin working on their first project, which will involve creating a simple 3D model using Blender AI. Weeks 3-4: Character Design and Modeling In weeks 3 and 4, students will be introduced to the principles of character design and modeling. This will include an overview of the design process, character anatomy, and the basics of 3D modeling. Students will also be introduced to the Midjourney software tool, which will be used for character design. During this section, students will work on designing and modeling their own original characters. Weeks 5-6: Environment Design and World Building During weeks 5 and 6, students will learn about environment design and world building. This will include an introduction to mood board creation, environmental storytelling, and the creation of assets for use in environments. Students will also begin to work on designing and building their own environments using Blender AI. Weeks 7-8: Special Effects and Simulation In weeks 7 and 8, students will learn about special effects and simulation. This will include an introduction to Stable Diffusion software tool, which will be used for creating special effects. Students will work on adding special effects to their characters and environments. Weeks 9-10: Crowd Scene and Motion Capture In weeks 9 and 10, students will learn about crowd scenes and motion capture. This will include an introduction to the Point-E and PifuHD software tools, which will be used for motion capture and facial expression transfer. Students will work on adding motion capture to their characters and creating a crowd scene. Weeks 11-12: Sound Design and Video Compositing In weeks 11 and 12, students will learn about sound design and video compositing. This will include an introduction to sound design principles and the use of sound in animation, as well as an introduction to the Kdenlive software tool, which will be used for video compositing and editing. Students will work on creating their own sound design and integrating it into their final project. Weeks 13-14: Texture, Lighting, and Rendering In weeks 13 and 14, students will learn about texture, lighting, and rendering. This will include an introduction to texture creation and editing using Krystal Office+(GIMP, Krita, and Inkscape), as well as an introduction to lighting and rendering in Blender AI. Students will work on adding textures, lighting, and rendering to their final project. Weeks 15-16: Final Graduation Project During the final two weeks of the course, students will work on their final graduation project. This will involve using all the skills and tools they have learned throughout the program to create a high-quality CG feature animation. Students will be required to submit a completed project that meets certain quality standards, which will be outlined in the project guidelines. Throughout the course, students will have access to additional resources and materials, such as video tutorials and online forums, to support their learning and development. The course will also include regular assessments and feedback to help students track their progress and identify areas where they need to improve.
This camp allows participants to experience data analysis and decision-making using Python. Even if you have no prior experience with Python, you can learn it comfortably in this camp. Our instructors will guide students through the basics of Python, starting with basic syntax, and then lead them through more complex data analysis operations in a hands-on setting. At the end of the camp, students will be required to complete a knowledge assessment to demonstrate their knowledge mastery. (Course Target Audience: People who have frequent contact with data and have basic concepts and understanding of data analysis and are interested in strengthening their data visualization, analysis and decision-making skills. Target group: People who need to work with data or who want to join or want to join the data analysis industry Duration: 40 hours Teaching method: Classroom, demonstration and practice Requirements for the certificate: Students must meet the following graduation requirements in order to receive a certificate of completion. (i) the total attendance must meet the minimum requirement (80%) of the course; and (ii) must receive an overall passing grade on the course evaluation; and (iii) must receive a passing grade on the final examination. Course contents are shown as below: 1. Python basic grammar and application training (10 hrs) a. Python Basic Grammar b. Use advanced Python to process table formatting c. Extract data from API via Python 2. Data analysis and decision-making training (28 hrs) a. The nature of data and its application b. Using basic tools to explore and describe data c. Use visualization tools d. Understanding and Interpreting Data e. Presentation of latest data analysis f. Development of key concepts of data and data analysis g. Data analysis and modeling h. Visualization and presentation of data insights 3. Assessment- final Exam (2 hrs))
There are various ways to study financial markets and the DuPont Analysis can be useful for understanding the particular components which are driving company profits. The DuPont Analysis formula is a tool that can help avoid misleading conclusions regarding a company’s profitability. In this course, investors will learn how to read and interpret the financial reports of public listed companies. By using the DuPont formula to build a simple table in 10 minutes, investors can also learn to seek for undervalued companies and avoid overvalued companies.
Although trading is a process between subjective humans, the market itself is objective and unbiased. One's perception of the market is completely up to oneself. If your goal in the long run is to attain and maintain the status of a trader in the market, it is crucial to develop a mindset that helps you to observe the market from an unbiased perspective. In this course, you will learn methods to remove subjective conceptions of the market and analyze objectively facts from multiple perspectives before performing trade.
In this course, you will learn core animation principles starting from simple bouncing ball animations to more advanced character model movements such as walking, jumping and acting. Students will also be guided through the animation workflow and technical terminology to help them adapt to the professional animation scene more quickly. This course is designed for beginners without prior experience, and who harbor a strong interest in 3D animation.
This course is aimed at beginners in Blender who wish to build simple assets for their games. From learning the ropes in Blender to importing your very own game assets into a game engine of your choice, this course shall serve as your complete guide to making game assets in Blender.
This course shall help beginners new to Blender's Grease Pencil tool quickly grasp its basic functions and applications. Students will learn how to use Drawing Mode, edit drawings, choose the right brushes and materials, add modifiers and shaders, make 2D animations and more.
This course offers a comprehensive guide to motion graphic techniques using Blender. Using Blender productions as examples, individual shots and the techniques used, the effects they create shall be carefully dissected and analysed. By the end of this course, you will be able to master these motion graphic techniques and apply them to your own productions. The course is designed for complete beginners in motion graphics and who are interested in creating them on Blender.
This course assumes that you have some knowledge of using Blender. You will learn about rigging tools in Blender Studio, as well as the rig generation workflow with Rigify. What is Rigify? The add-on enables you to input parameters on a simple Metarig, which is used to generate the Control Rig that you will use to control your character. The entire process will be instructed to you in detail by our experienced intructors during the course.
