Taught In:
company training
Levels:
Level of expertise and familiarity the material in this course assumes you have. The greater the amount of introductory material taught in the course, the less you will need to be familiar with when learner attend.
Participants:
This course will be useful to business leaders, operations and product managers, entrepreneurs, consultants, working professional without technical background, and solution-builders with data and developing on want to learn how AI and ML solutions can be built without code platform. As organizations realize this, no-code approaches to implementing emerging technologies are becoming popular and essential to know. A no-code approach to data science and AI can be a game-changer. A courses to utilize the full power of AI and build intelligent solutions from data without having to write a single line of code.
SyllabusCourse Overview:
In this course, participants will learn to use Artificial Intelligence (AI) and Machine Learning (ML) to make data-driven business decisions by understanding the theory and practical applications of supervised and unsupervised learning, neural networks, recommendation engines, computer vision, etc. Leverage the power of AI and Data Science (DS) without writing a single line of code.
This course leverages leadership in innovation, science, engineering, and technical disciplines developed over years of research, teaching, and practice. Great learning collaborates with institutions to manage enrollments, technology, and participant support.
Methods:
The course is taught from traditional classroom lectures and riveting discussions to group projects to engaging and interactive simulations and exercises with your peers. An interactions by demonstrations, experiments and simulations itself.
Learning OutcomesOutcomes:
The fundamentals of DS solutions without code AI and ML will help participants on:
- Gain a holistic understanding of AI landscape for variety of business use cases.
- Gain strong conceptual understanding of most widely used algorithms
- Ability to build practical AI solutions using no code tool.
- Gain practical insights into various nuances involved in implementing AI solutions in the industry.
- Develop critical thinking and problem solving skills required to tackle business problem with AI.
The course will begin with blended learning elements, including case studies, projects, learning sessions, and presentations by participants. Therefore, the course major will get distributed in the following manner:
Lec 01 – Introduction to AI Landscape
Lec 02 – Data Exploration – Structured Data, Networks, and Graphical Models
Lec 03 – Prediction Methods – Regression
Lec 04 – Decision Systems
Lec 05 – Data Exploration – Unstructured Data
Lec 06 – Recommendation Systems
Lec 07 – Data Exploration – Temporal Data
Lec 08 – Prediction Methods – Deep Learning and Neural Networks
Lec 09 – Computer Vision Methods
Lec 10 – Workflows and Deployment