Mastering Machine Learning: A Comprehensive 8-Week Program

Dropledge Academy
Last Update October 26, 2024
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About This Course

Upon successfully completing this course, participants will be awarded a Certificate of Achievement, showcasing their mastery of Machine Learning techniques and tools, boosting their professional profile in the fast-evolving tech landscape.

Certificate of Achievement
Upon completion of the course, learners will receive a Certificate of Achievement enhancing their credentials in the digital economy.

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Learning Objectives

Master Machine Learning Essentials: Build a solid foundation in machine learning, covering supervised, unsupervised, and reinforcement learning, along with key concepts like features, labels, models, and predictions.
Hands-On Learning: Gain practical experience through real-world case studies and projects, enabling you to apply theoretical knowledge to real-world problems.
Tailored Curriculum: Follow a flexible learning path customized to your background, whether you're a beginner or advancing to professional-level techniques.
Advanced Techniques: Delve into deep learning, neural networks, transfer learning, and GANs, staying current with the latest industry advancements.
Ongoing Support: Benefit from continuous guidance from expert instructors, with personalized mentorship to help you stay on track and meet your learning goals.
Career & Industry Insights: Access sessions focused on career paths, industry trends, and best practices in AI to help you make informed decisions in a rapidly evolving field.
Structured Progression: Learn systematically from basic to advanced levels, ensuring a comprehensive grasp of machine learning concepts and techniques.

Target Audience

  • Students: Must understand math basics (linear algebra, calculus, probability), be proficient in programming (especially Python), and have a good grasp of algorithms and data structures.
  • Industry Professionals: Should possess programming skills, be well-versed in data tools, and have practical machine learning experience.

Curriculum

28 Lessons

Week 1: Fundamentals of Machine Learning

Introduction to machine learning and its applications00:00:00
Understanding supervised, unsupervised, and reinforcement learning00:00:00
Overview of key concepts: features, labels, models, and predictions00:00:00

Week 2: Data Preprocessing

Week 3: Supervised Learning

Week 4: Unsupervised Learning

Week 5: Introduction to Deep Learning

Week 6: Deep Learning Advancement

Week 7: Machine Learning Pipeline

Week 8: Machine Learning – Case Studies

Digital transformation concept. Binary code. AI (Artificial Intelligence).

£375.00

Level
Intermediate
Lectures
28 lectures
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