Requirements

• There is no specific prerequisite to learn machine learning. But you need to be from engineering/science/Maths/Stats background to understand the theory and the techniques used. You need to be good in mathematics. If you are not
• still you can machine learning
• but you will face difficulty when solving complex real world problems. Many say you need to know Linear algebra
• Calculus etc. etc. but I never learnt it
• yet I am able to work on machine learning.

Description

Course Description:

Are you ready to dive into the world of Artificial Intelligence and develop practical skills in Machine Learning and Deep Learning? This comprehensive course is designed to take you on an exciting journey through the realms of AI, enabling you to create real-world projects from scratch.

In this hands-on course, you'll embark on a dynamic learning experience where you'll build and deploy a series of Machine Learning and Deep Learning projects, starting from the very basics and progressing to advanced applications. Whether you're a beginner looking to get started in AI or an experienced practitioner aiming to expand your project portfolio, this course caters to all levels of expertise.

Key Highlights:

- Project-Centric Learning: This course revolves around project-based learning. You won't just study theory; you'll apply your knowledge to solve practical problems. Each module introduces a new project, ensuring you gain practical experience.

- From Fundamentals to Mastery: We begin with the fundamentals, ensuring that even beginners can grasp the concepts. As the course progresses, we delve into advanced topics, equipping you with the skills needed to tackle complex AI challenges.

- Wide Range of Applications: You'll explore a diverse range of applications, including image classification, natural language processing, recommendation systems, and more. These projects mirror real-world scenarios, providing valuable insights into AI's versatility.

- Deep Dive into Deep Learning: Deep Learning is a core component of modern AI. You'll work with neural networks, convolutional networks, and recurrent networks, and explore cutting-edge techniques to tackle complex tasks.

- Deployment and Scaling: It's not enough to build models; you'll also learn how to deploy them, making your projects accessible to a wider audience. You'll explore cloud-based solutions and scaling strategies.

- Collaborative Environment: Engage with fellow learners in a collaborative environment. Share your insights, seek assistance, and collaborate on group projects, mimicking the collaborative nature of AI development in the real world.

- Mentorship and Support: Experienced AI practitioners and instructors will guide you throughout the course. You'll receive expert insights and feedback to help you refine your projects.

Upon completion of this course, you'll emerge with a robust AI portfolio, showcasing your ability to create intelligent solutions from the ground up. Whether you aspire to work in AI research, and data science, or simply want to harness the power of AI for your projects, this course equips you with the skills and confidence to succeed in the world of Machine Learning and Deep Learning. Join us on this exciting journey into the realm of AI, and let's build the future together, one project at a time!

Who this course is for:

• Beginner into Machine Learning
• Beginner into Python
• Fresher to get job into Machine Learning Engineer
• Career transition from Non Technical into Data Science