and Machine Learning I.
100 % Online | 1 month or less | 15 mins a day (Micro-learning)
15 Mins Per Day
About this course
Are you looking to dive deep into the world of Artificial Intelligence (AI) and Machine Learning (ML)?
As we navigate the modern digital era, understanding AI and ML is becoming crucial, not just for tech experts but for professionals across fields. This course, "Artificial Intelligence and Machine Learning I", is tailored to guide you through the fascinating journey of AI and its evolution.
Delve into the rich history of AI, grasp the distinctions between AI, machine learning, and deep learning, and understand the technical methodologies that power these innovations. Discover how AI plays a pivotal role in robotics and integrates seamlessly with big data. Learn practical techniques, such as how to work with diverse datasets, clean continuous and categorical data, and select the most suitable algorithm for your specific challenges.
From decision trees and support vector machines to advanced boosting models, this course provides a comprehensive overview of essential ML tools. Tackle common challenges, understand the nuances of overfitting vs. underfitting, and master the art of tuning hyperparameters. Whether you're aiming to apply ML principles, discern various machine learning types, or ascertain the pros and cons of logistic regression, this course has you covered.
By the end of this course, you'll not only be familiar with the foundations of AI and ML but also be equipped with the knowledge to evaluate models effectively, discern between models and algorithms, and make informed decisions in AI-driven contexts. Embark on this transformative journey and unlock the power of Artificial Intelligence and Machine Learning.
What you'll learn
- The history of AI, Technical approaches to AI
- Integrating AI with big data, Describing how to work with data
- What is machine learning (ML), ML vs. deep learning vs. AI
- Applying machine learning principles
- Distinguish different types of machine learning
- Identifying problems that use machine learning
- Create decision trees, Explain how to select the best algorithm
- Handling common challenges in ML
- Measuring success
- Evaluating a model, Models vs. Algorithms
- and many more
Artificial Intelligence and Machine Learning I.
Duration: 7.5 hours (self-paced)
In every daily block you will find different types of study materials on the particular theme of the module. Lessons consist of:
- Audio-Visual materials
- Additional tips for relevant and interesting ebooks, videos or web pages
- Short tests to evaluate your progress
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Enroll this course by filling the form below and proceeding with a payment.
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OUR APPROACH TO ONLINE EDUCATION
Our courses consist of daily short lessons which follow the principles of microlearning. It is then easy to find time every day, maintain focus and learn what you need in practice.
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