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What is Machine Learning ?

Machine Learning is a branch of AI that enables computers to learn from data, identify patterns, and make predictions or decisions without explicit programming. It uses algorithms to train models on large datasets, allowing machines to improve their performance over time and perform tasks like image recognition, speech processing, and predictive analytics.

Description

Our thorough course introduces Machine Learning. Through real examples and projects, learn key ideas, algorithms, and approaches. This training is for beginners and experts. Learn to design and deploy Machine Learning models for image recognition, NLP, recommendation systems, and more.

SKILLS COVERED
  • Fundamentals of Machine Learning
  • Supervised learning algorithms
  • Unsupervised learning algorithms
  • Reinforcement learning principles
  • Data pre-processing and feature engineering
  • Evaluation metrics for model performance
  • Building and training machine learning models
  • Application of machine learning in image recognition
  • Natural language processing techniques
  • Recommendation systems development.
1. Introduction to Machine Learning
  • Overview of Machine Learning concepts and applications
  • Types of Machine Learning algorithms
  • Understanding the data-driven approach
2. Supervised Learning
  • Regression algorithms
  • Classification algorithms
  • Model evaluation and selection
3. Unsupervised Learning
  • Clustering algorithms
  • Dimensionality reduction techniques
  • Anomaly detection
4. Reinforcement Learning
  • Markov decision processes
  • Q-learning and policy gradients
  • Model-free and model-based approaches
5. Data Pre-processing and Feature Engineering
  • Handling missing data and outliers
  • Feature scaling and normalization
  • Feature selection and extraction techniques
  • 6. Model Evaluation and Performance Metrics
    • Cross-validation techniques
    • Evaluation metrics for regression and classification
    • Bias-variance trade-off
    • 7. Introduction to Deep Learning
      • Neural networks and their architecture
      • Activation functions and backpropagation
      • Deep learning libraries and frameworks
      • 8. Natural Language Processing
        • Text pre-processing and tokenization
        • Sentiment analysis and text classification
        • Language generation and machine translation
        • 9. Recommendation Systems
          • Collaborative filtering
          • Content-based filtering
          • Hybrid recommendation approaches
          • 10. Applied Machine Learning Projects
            • Image recognition and computer vision
            • Predictive analytics and time series forecasting
            • Industry-specific applications
            • 11. Ethical Considerations in Machine Learning
              • Bias and fairness in machine learning models
              • Privacy and security implications
              • Responsible AI and ethics guidelines
              12. Case Studies and Practical Examples
              • Real-world applications of Machine Learning
              • Hands-on implementation exercises
              13. Final Assessment and Certification
              • Comprehensive evaluation of knowledge and skills
              • Awarding of completion certificate for successful participants
Advanced Certification in Machine Learning
  • Completion Certificate in Machine Learning
  • Machine Learning Specialist Certification
  • Advanced Machine Learning Certification
  • Professional Certification in Data-driven Decision Making
  • Certified Machine Learning Practitioner
  • Machine Learning for Business Certification
  • Deep Learning and Neural Networks Certification
  • Natural Language Processing Certification
  • Recommendation Systems Certification
  • Ethical AI and Machine Learning Practices Certification.

While prior programming experience can be beneficial, it is not a strict requirement. Basic knowledge of programming concepts, such as variables, loops, and functions, will help you grasp the course material more easily. However, we provide introductory material to get you started with programming if you are a beginner.

The course primarily utilizes Python, a widely-used programming language in the field of Machine Learning. We will also introduce popular libraries and frameworks such as TensorFlow, scikit-learn, and Kera’s. These tools are essential for building and training machine learning models.

For the majority of the course, a computer with a modern operating system (Windows, macOS, or Linux) and a stable internet connection will suffice. We will guide you through the installation process of the necessary software and libraries. It is recommended to have a machine with reasonable processing power to handle training larger models effectively.

There are no strict prerequisites for this course. However, a basic understanding of mathematics, including concepts such as algebra, calculus, and probability, will be beneficial. Additionally, familiarity with Python programming language or any other programming language is advantageous.

Yes, you will have lifetime access to the course materials, including lecture videos, slides, and code examples. You can revisit the content at any time to reinforce your knowledge or refer back to specific topics.

Yes, upon successful completion of the course and meeting the requirements, you will receive a completion certificate. This certificate will serve as evidence of your proficiency in Machine Learning and can be a valuable addition to your resume or professional profile.

Absolutely! Our team of experienced instructors and support staff will be available to assist you throughout the course. You can ask questions, seek clarifications, and engage in discussions through dedicated forums or Q&A sessions.

The course duration can vary depending on your learning pace and the time you dedicate to the course. On average, participants complete the course within a few weeks by devoting a few hours per week.

However, you can learn at your own pace, and you will have lifetime access to the course materials, allowing you to learn at your convenience.

While this course does not guarantee job placement, we provide guidance on career paths in Machine Learning and share industry insights and trends. We offer advice on building a strong Machine Learning portfolio and showcasing your skills effectively.

We strive to deliver high-quality content and ensure your satisfaction with the course. However, if you are not satisfied within a certain time frame after enrollment, please refer to our refund policy for more information.
Raghava

"Hi folks! I thank to Korsuliv's Machine Learning course. Raghava here. Korsuliv got me a great HP job! It was amazing. They covered algorithms to actual datasets. Korsuliv is the venue for machine learning enthusiasts like myself. They'll improve your talents!"

Anusha

"Hello, everybody! My success story was too exciting to keep to myself. I’m Anusha, I got a job at HP owing to Korsuliv's Machine Learning course. This course transformed me. They taught me data preparation and modelling. Best part? Real project experience made me job-ready. Korsuliv is the means to enter into machine learning and get into major firms like HP. They will rock your world!"

Demo Class
23 Nov 2024

08:00 AM TO 11:00 AM IST

24 Nov 2024

08:00 AM TO 11:00 AM IST

Key Highlights

6-month comprehensive curriculum for Python.

100% live sessions for an interactive learning experience.

Hands-on workstations and live projects to apply knowledge.

Personalized mentoring and interview preparation with 5 mock and 10 actual interviews.

Recognized certification and career support and alumni network

24X7 Learner’s Support

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