Machine Learning Engineer

Machine learning engineers uses Data, Artificial Intelligence, and Algorithms in their job. An essential component of the data science team are machine learning engineers. Their responsibilities include studying, creating, and constructing artificial intelligence, which is in charge of machine learning as well as upkeep and enhancement of already-existing AI systems.

Who is the Course for?

• The course is for individuals interested in pursuing a career as a Machine Learning Engineer, whether they have prior experience in programming, mathematics, or data science or are newcomers eager to enter the field. It’s designed for tech enthusiasts, professionals seeking to upskill, and graduates looking to specialize in machine learning.

What you will learn:

•  The fundamentals of machine learning algorithms, How to build, train, and evaluate machine learning models, Python programming for machine learning (including libraries like TensorFlow, PyTorch, and Scikit-learn), Data preprocessing and feature engineering, Deep learning concepts and neural networks, Model deployment and scaling in production environments, Best practices for optimizing and tuning models, Problem-solving with real-world datasets, Ethical considerations and bias in machine learning

Skills you will acquire

• Building and deploying machine learning models
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn)
• Data preprocessing and feature engineering
• Deep learning and neural network implementation
• Model evaluation, tuning, and optimization
• Problem-solving with real-world datasets
• Understanding of production environments and deployment
• Ethical decision-making in machine learning
• Effective collaboration with data teams and stakeholders
• Industry you can work in with the skills: Same above….