Udemy

AI Engineer Explorer Certificate Course

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  • 12,266 Students
  • Updated 6/2025
  • Certificate Available
4.5
(158 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
12 Hour(s) 41 Minute(s)
Language
English
Taught by
School of AI
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.5
(158 Ratings)

Course Overview

AI Engineer Explorer Certificate Course

Build Your AI Foundation with Python, Data Science, Math & Machine Learning Basics

Are you ready to take your first step into Artificial Intelligence and become an AI Engineer? The AI Engineer Explorer Certificate Course is your gateway into the exciting and fast-growing world of AI, Machine Learning, and Data Science. Designed for beginners, this hands-on course equips you with the foundational skills you need to start your journey toward becoming a skilled AI developer or AI product builder.

In this course, you will begin with Python Programming Basics for AI. Python is the most popular programming language in the AI world today. You will learn how to write clean Python code, understand variables, loops, functions, and object-oriented programming—laying the groundwork for building real AI applications.

Next, you’ll dive into Data Science Essentials for AI, where you will explore data preprocessing, data visualization, and exploratory data analysis (EDA) using tools like Pandas, NumPy, and Matplotlib. Understanding how to work with data is critical in AI, and this section ensures you gain practical, job-ready experience.

Then, you’ll master the Mathematics for Machine Learning and AI—a core pillar for any serious AI professional. We break down the essentials of linear algebra, calculus, and matrix operations in a way that is intuitive and application-oriented, helping you build strong analytical thinking.

You will also cover Probability and Statistics for Machine Learning, which is crucial for understanding how AI models learn from data. Topics include Bayes’ Theorem, distributions, standard deviation, confidence intervals, and hypothesis testing—all taught with AI-centric examples that make complex concepts feel natural.

Finally, you'll step into the world of Machine Learning itself. In the Introduction to Machine Learning, you’ll learn how algorithms like linear regression, classification, and clustering work under the hood. You’ll also use Scikit-learn to train and evaluate simple ML models, gaining firsthand experience in how machine learning pipelines are built.

By the end of the AI Engineer Explorer Certificate Course, you’ll have a strong grasp of the core concepts of AI, and be well-prepared to move into more advanced topics like Deep Learning, Natural Language Processing, and AI product development. Whether you're a student, software developer, career changer, or tech enthusiast, this course gives you a structured, easy-to-follow path to build your AI foundation.

  • No prior experience required

  • Hands-on projects included

  • Certificate of Completion

  • Ideal for AI beginners, data science aspirants, and future AI product managers

Take your first step into the future—join thousands of learners and start your journey to becoming a certified AI Engineer today.

Course Content

  • 7 section(s)
  • 37 lecture(s)
  • Section 1 Introduction to Course and Instructor
  • Section 2 Python Programming Basics for Artificial Intelligence
  • Section 3 Data Science Essentials for Artificial Intelligence
  • Section 4 Mathematics for Machine Learning and Artificial Intelligence
  • Section 5 Probability and Statistics for Machine Learning and Artificial Intelligence
  • Section 6 Introduction to Machine Learning
  • Section 7 Quiz and Congratulations

What You’ll Learn

  • Write clean Python code for AI applications using variables, loops, functions, and OOP
  • Analyze and manipulate data with Pandas and NumPy
  • Visualize datasets using Matplotlib and Seaborn
  • Understand core math concepts like linear algebra and calculus for AI
  • Apply probability theory and statistics to AI problem-solving
  • Explain how machine learning models work and are trained
  • Build and evaluate basic ML models using Scikit-learn
  • Develop a solid foundation to pursue advanced AI and ML topics


Reviews

  • R
    Rohit
    4.5

    it's excelent

  • K
    Kushalta Bhattarai
    5.0

    Very good course for beginners.

  • V
    Vikas Sharma
    4.5

    good explanation of things able to catchup with no time

  • V
    Vedant Jadhav
    5.0

    Well! I Just Loved the Course! The Way it is organized, The way it was taught by instructor, Just Loved It! I Really have to Say that This Course is hidden Gem if you want to start you career in Artificial Intelligence and machine Learning. It helped me a lot ! Thank You for this Course!

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