Introduction to AI & ML

  • BeginnerLevel

  • 23281+Students Enrolled

  • 1 HrDuration

  • 4.9Average Rating

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About this Course

  • Understand the core principles of Artificial Intelligence and Machine Learning, including how machines learn from data and improve performance over time.
  • Learn the key differences between AI, Machine Learning, and Deep Learning, and where each is used in real-world systems.
  • Gain clarity on types of Machine Learning (supervised, unsupervised, and reinforcement learning) and the problems each approach is best suited for.
  • Explore how data, algorithms, and models work together to build intelligent systems.
  • Understand common AI and ML terminologies such as models, training, inference, features, and predictions.
  • Learn how AI and ML are applied in real-world use cases like recommendation systems, fraud detection, image recognition, and natural language processing.
  • Develop the ability to identify problems that can be solved using AI and ML, and recognize situations where they should not be applied.
  • Build a strong conceptual foundation for advanced AI, machine learning, data science, and generative AI learning paths.

Learning Outcomes

AI & ML Fundamentals

Understand core concepts, workflows, and foundations of AI and ML

AI vs ML vs Deep Learning

Clearly differentiate intelligent systems and learning approaches

ML Foundations

Learn how models train, learn patterns, and make predictions

Real-World AI Application

Apply AI and ML concepts to practical industry use cases

Who Should Enroll

  • Ideal for individuals seeking to enhance their expertise and integrate AI and ML into their current roles.
  • Perfect for those new to AI and ML, aiming to build foundational knowledge and step into the growing industry.
  • Suitable for professionals in various fields to leverage AI/ML in their decision-making and workflows

Course Curriculum

This Introduction to AI and ML course gives a beginner-friendly overview of the fields, covering core concepts, tools, and real-world applications. It builds a strong foundation to understand how AI and ML systems work.

tools

  1. 1. Module 1: Introduction to AI & ML

  2. 2. What is AI&ML?

  3. 3. Types of ML

  4. 4. When to Apply AI&ML

  5. 5. Recent AI Uprising

  6. 6. How the world is Changing?

  7. 7. Building Blocks of AI and ML

  8. 8. Knowing Each Other

  9. 9. AI&ML Blackbelt Plus Program (Sponsored)

  1. 1. Common Terminologies

  2. 2. Common Data Capturing Types and Tools

  3. 3. Common Tools

  4. 4. Common Techniques

  5. 5. Common Techniques - Part1

  6. 6. Common Techniques - Part2

  1. 1. Skills Required in Data Science

  2. 2. AI and ML Black Belt+

  3. 3. Where to Go from here!!

Meet the instructor

Our instructor and mentors carry years of experience in data industry

company logo
Kunal Jain

Founder & CEO Analytics Vidhya

Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- the world's 2nd largest Data Science community.

Get this Course Now

With this course you’ll get

  • 1 Hour

    Duration

  • Kunal Jain

    Instructor

  • Beginner

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Industry-Recognized Credential
  • Career Advancement Credential
  • Shareable Achievement
certificate

Frequently Asked Questions

Looking for answers to other questions?

Artificial Intelligence is the broader concept of creating intelligent systems, while Machine Learning is a subset of AI that enables systems to learn from data and improve automatically.

Yes, this course is designed for absolute beginners and requires no prior experience in programming, AI, or machine learning.

No prior programming knowledge is required, as this course focuses on building strong conceptual foundations first.

You will learn AI and ML fundamentals, types of machine learning, real-world applications, tools, and career pathways.

AI and ML are used in recommendation systems, fraud detection, image recognition, voice assistants, and predictive analytics.

AI and ML are widely used in healthcare, finance, retail, marketing, manufacturing, and technology.

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