Certified Professional in Reinforcement Learning Fundamentals
-- viewing nowReinforcement Learning (RL) is rapidly transforming industries. This Certified Professional in Reinforcement Learning Fundamentals program provides a strong foundation.
4,330+
Students enrolled
7-Day Money-Back Guarantee
Enroll with confidence
Secure Checkout
256-bit encrypted payment
Lifetime Access
Learn at your own pace
About this course
100% online
Learn from anywhere
Shareable certificate
Add to your LinkedIn profile
2 months to complete
at 2-3 hours a week
Start anytime
No waiting period
Course Details
- Introduction to Reinforcement Learning: Markov Decision Processes (MDPs), agents, environments, rewards
- Dynamic Programming Algorithms: Value iteration, policy iteration, their applications and limitations
- Monte Carlo Methods: Prediction and control using Monte Carlo techniques, importance sampling
- Temporal Difference Learning: SARSA, Q-learning, Expected SARSA, and their convergence properties
- Deep Reinforcement Learning: Introduction to Deep Q-Networks (DQN), experience replay, target networks
- Policy Gradient Methods: REINFORCE, actor-critic methods, advantages and disadvantages
- Advanced Reinforcement Learning: Exploration-exploitation trade-off, function approximation, eligibility traces
- Reinforcement Learning Applications: Case studies in robotics, game playing, resource management
- Reinforcement Learning Environments: Gym, Unity ML Agents, other relevant platforms and their usage
Career Path
Career Role Description Reinforcement Learning Engineer (UK) Develops and implements RL algorithms for real-world applications, focusing on optimization and control.
High demand in autonomous systems and robotics.
Machine Learning Engineer with Reinforcement Learning Expertise (UK) Applies RL techniques within a broader ML context, often involving deep learning models and large datasets.
Strong problem-solving skills are key.
Data Scientist specializing in Reinforcement Learning (UK) Uses RL methods for data analysis and predictive modeling, extracting insights from complex data structures.
Requires strong statistical knowledge.
AI Research Scientist focusing on Reinforcement Learning (UK) Conducts cutting-edge research in RL algorithms and theory.
Publishes findings and contributes to advancements in the field.
Requires a PhD.
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
Why people choose us for their career
Loading reviews...
Frequently Asked Questions
Course fee
- 3-4 hours per week
- Early certificate delivery
- Open enrollment - start anytime
- 2-3 hours per week
- Regular certificate delivery
- Open enrollment - start anytime
- Full course access
- Digital certificate
- Course materials
Get course information
Earn a career certificate
