Machine Learning Essentials
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10,000+
Learners -
Fundamentals
Level -
3+
Hours -
75
Lessons -
Flexible
Learning
Trusted by employees at leading organizations
CHARGE AHEAD IN YOUR MACHINE LEARNING CAREER
Machine learning offers the foundation for the growth of the AI landscape. Rely on our new machine learning course to craft your journey as an ML expert.
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Explore the implications of supervised, unsupervised, and reinforcement learning in diverse real-world use cases.
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Leverage ML algorithms like decision trees, neural networks, and support vector machines for different tasks.
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Implement evaluation metrics like precision and recall to measure the performance and reliability of models.
Take One Step towards a Successful ML Career with the ML Essentials Course
Machine learning is the cornerstone of the technological revolution as it provides the core components to build AI solutions. The new machine learning essentials course gives you a comprehensive resource to learn how to use machine learning algorithms in different real-world problems. With the average annual salary of an ML expert at $130,000, learners can find promising opportunities for expanding their careers.
As the AI revolution gains momentum, ML experts have become the most valuable assets for businesses working with AI technologies. The impact of machine learning on different industries such as healthcare, manufacturing, and supply chain management calls forthe introduction of new job roles. The FSA machine learning course gives you the perfect start as a beginner by introducing you to the fundamental concepts of machine learning.
The lessons of the course focus on crucial topics in machine learning that you must know as an ML professional. The new ML training course helps you understand how supervised, unsupervised, and reinforcement learning work in the context of real-world problems. This course also sheds light on common ML algorithms and techniques to evaluate and validate machine learning models. Most important of all, the emphasis on practical learning in the course empowers learners to use their skills effectively to solve business problems.
WHAT YOU WILL LEARN?
Transform Your Career Trajectory with the Knowledge of…
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Introductory topics and concepts in machine learning
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Importance of supervised learning
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Applications and examples of unsupervised learning
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Use cases of reinforcement learning
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ML techniques for predictive analytics and optimization
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Methods for model evaluation and validation
Become a Trusted ML Expert for Every Business with…
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Knowledge of fundamental machine learning concepts
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Skills to use supervised learning in real-world applications
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Ability to leverage unsupervised learning in specific use cases
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Fluency in the reinforcement learning approach
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Capabilities to use popular ML algorithms and core techniques
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Know-how of best practices to evaluate ML models with metrics
Course Curriculum
- A message from the instructor
- Disclaimer
- Download Course Presentation
- Module Overview
- What is Machine Learning?
- History and Evolution of Machine Learning
- Types of Machine Learning
- Applications of Machine Learning
- Key Terminologies in Machine Learning
- How Machine Learning Works
- Challenges in Machine Learning
- Hands-on Exercise: Load and Explore a Dataset
- Module Summary
- Interactive Exercise
- Module Overview
- Overview of Supervised Learning
- Linear Regression
- Hands-on Exercise: Linear Regression
- Logistic Regression
- Hands-on Exercise: Logistic Regression
- Decision Trees
- Support Vector Machines (SVM)
- Hands-on Exercise: SVM
- K-Nearest Neighbors (KNN)
- Model Evaluation in Supervised Learning
- Module Summary
- Interactive Exercise
- Module Overview
- Overview of Unsupervised Learning
- Clustering: K-Means
- Hands-on Exercise: K-Means Clustering
- Clustering: Hierarchical Clustering
- Hands-on Exercise: Hierarchical Clustering Exercise
- Association Rule Learning
- Principal Component Analysis (PCA)
- Anomaly Detection
- Model Evaluation in Unsupervised Learning
- Module Summary
- Interactive Exercise
- Module Overview
- Introduction to Reinforcement Learning
- Key Concepts in Reinforcement Learning
- Markov Decision Processes (MDPs)
- Hands-on Exercise: MDPs
- Exploration vs. Exploitation
- Q-Learning
- Deep Q-Networks (DQNs)
- Applications of Reinforcement Learning
- Module Summary
- Interactive Exercise
- Module Overview
- Introduction to Regression & Classification
- Simple Linear Regression
- Multiple Linear Regression
- Logistic Regression for Classification
- Genetic Algorithms
- Hands-on Exercise: Genetic Algorithm
- Module Summary
- Interactive Exercise
- Module Overview
- Introduction to Model Evaluation
- Training and Testing Data
- Cross-Validation Techniques
- Confusion Matrix
- Hands-on Exercise: Model Evaluation
- Precision, Recall, and F1 Score
- ROC Curve and AUC
- Bias-Variance Tradeoff
- Hands-on Exercise: ROC-AUC and Bias Variance Tradeoff
- Module Summary
- Interactive Exercise
- Module Overview
- Course Summary
- Final Exam and Next Steps
- Exam Details
- Final Exam
- Bonus: Download Machine Learning Glossary
NAVIGATE THE AI LANDSCAPE AS AN ML EXPERT- WHO SHOULD JOIN?
Software developers and engineers must use the machine learning course to explore new career opportunities.
Information technology professionals can rely on this course to develop more efficient and powerful solutions.
Innovation managers and entrepreneurs should adopt this course as a manual to craft innovative ML solutions for real-world problems.
Anyone who wants to explore the AI and ML landscape will find this course helpful for learning the basic concepts.
TAP INTO EVERY CAREER OPPORTUNITY IN MACHINE LEARNING- CLOSE THE SKILL GAP
The ML essentials course is a fresh attempt at introducing everyone to the world of machine learning and artificial intelligence. The lessons covered in the course focus on different machine learning types, algorithms, and techniques. Learners can capitalize on the demonstrations and interactive exercises for a hands-on learning experience with the course. Once you complete this course, you will have the confidence to solve real-world machine learning problems in diverse roles.
Get Started Bonus Material
Course Presentation
Download the course presentation for the convenient access anywhere, anytime.
Additional Lectures
Gain access to complimentary additional lectures and enhance your understanding.
Join Online Events
Learn from industry experts in AI and enhance your knowledge.
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Machine Learning Essentials Course FAQs
The new machine learning course helps you learn different types of machine learning approaches like supervised, unsupervised, and reinforcement learning. It also includes lessons on ML algorithms and the use of model evaluation metrics like precision and recall.
Yes, the course offers multiple benefits to business owners, especially in terms of productivity improvements. Business owners can encourage their teams to learn machine learning and discover new avenues to use machine learning for different business problems. In addition, businesses can use ML training as a valuable initiative to improve employee engagement.
The ideal candidates for the ML Essentials course are software developers or engineers, information technology professionals and innovation managers and entrepreneurs. Anyone who needs an introduction to the world of AI and ML is an ideal candidate for the course.
Yes, Future Skills Academy offers expert support for learners in the new machine learning essentials training course. You can find solutions to any doubt in the course topics or technical issues with the course from experts at FSA.
The different types of machine learning include supervised, semi-supervised and reinforcement learning. Each type of machine learning varies according to the data and method used for training ML models.
The ML Essentials course will help your career with comprehensive insights on how machine learning works. You can use the machine learning course with a certificate of completion to showcase your ML expertise. On top of it, the course prepares you with the skills to address real-world problems with machine learning.
The ML Essentials course is the perfect machine learning course for beginners as it does not have any eligibility criteria. Anyone can enroll in this course without prior knowledge of machine learning. However, knowledge of basic ML terminology will enhance your learning experience in this course.
The new ML course online is a self-paced training course and does not have any specific deadline to complete the course. You can learn all the lessons in the course at your own convenience and complete the final exam when you want.
Yes, the ML Essentials course is available with the FSA Premium Plan, which offers unlimited access to all courses in the FSA library.
Machine learning works through different stages, such as data collection and preparation, feature engineering and selection, and model selection and architecture. The subsequent steps include training and validation, model testing, and deployment.
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