Description
Global Certification Program
- E-Learning
- Globally lifetime Valid Certification
- Lifetime Valid Certification
- AI based Roleplay & Simulations
- Two Exam Attempts
Introduction
Certified Machine Learning Professional (CMLP)
In today’s world, where technology continues to shape industries and drive innovation, the importance of machine learning cannot be overstated. The GSDC Certified Machine Learning Professional (CMLP) is a highly in-demand certification exam that validates the skills and expertise of individuals in the field of machine learning. The ML Certification equips professionals with the knowledge and proficiency required to harness the power of machine learning in various domains. By demonstrating their competence through this machine learning professional certification, candidates showcase their ability to analyze vast amounts of data, develop predictive models, and make informed decisions. With the machine learning certification, individuals gain a competitive edge in the job market, opening up new career opportunities and enhancing their credibility as experts in the field. Stay ahead of the curve and unlock the potential of machine learning with the GSDC Certified Machine Learning Professional (CMLP) certification.
Learning Objective
❑ Master essential machine learning concepts and techniques.
❑ Develop predictive models using machine learning algorithms.
❑ Analyze and interpret large datasets for insights.
❑ Implement machine learning solutions in various domains.
❑ Optimize and fine-tune machine learning models.
❑ Evaluate and validate the performance of models.
❑ Apply ethical considerations in machine learning applications.
❑ Stay updated with the latest machine learning trends.
Curriculum
1. Introduction to Machine Learning
• What is Machine Learning?
• Definition of Big Data
• Big Data in Context with Machine Learning
• The Need to Understand and Trust Your Data
• Hybrid Cloud and Its Importance
• Leveraging the Power of Machine Learning
• When Statistics and Data Mining Team Up with Machine Learning
• Machine Learning in Context
• Approaches Towards Machine Learning
• Neural Networks and Deep Learning
2. Applying Machine Learning to Business Needs
• Understanding of customer dissatisfaction
• Recognizing the reason behind poor customer satisfaction
• Preventing Accidents from happening
• Advice for Applying Machine Learning
3. Looking Inside Machine Learning:
• The Impact of Machine Learning on Applications
• Data Preparation
• The Machine Learning Cycle
• Application Example: Photo OCR
4. Getting Started with Machine Learning
• Understanding How Machine Learning Can Help
• Focus on the Business Problem:
• Bringing Data Silos Together
• Avoiding Troubles to Occur
• Getting the Focus of Customers
• Machine Learning for Business
5. Learning Machine Skills:
• Determining the Skill That You Need
• Getting Educated
6. Business Problems That Can Be Solved Using Machine Learning:
• Applying Machine Learning to Patient Health
• Leveraging IoT to Create More Predictable Outcomes
• Proactively Responding to IT Issues
• Protecting Against Fraud
7. Ten Predictions on the Future of Machine Learning
• AI advancements are transforming industries through deep learning, automation, privacy-preserving techniques, and ethical regulations while ensuring responsible and impactful deployment.
