Video Training / IT and Programming for PC Tutorials →Machine Learning, Data Science A-Z AI with Python, AWS

Master Machine Learning and Data Science fundamentals
Build practical AI applications with Python by implementing real-world machine learning algorithms, deep learning basics
Develop end-to-end data science projects using industry-standard libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and PyTorch
Deploy AI and Machine Learning models on AWS by learning cloud-based ML services, model deployment, scalable inference, data storage

Requirements

No need to have any experience at all

Description

Unlock the power of Artificial Intelligence, Machine Learning, Data Science, and Cloud Computing with this comprehensive hands-on course designed for beginners, students, software developers, data analysts, and IT professionals. Whether you are starting your AI journey or looking to enhance your existing skills, this course provides a step-by-step learning path from the fundamentals to advanced real-world applications.
You will begin by learning Python programming for data science and machine learning, followed by data preprocessing, exploratory data analysis (EDA), feature engineering, data visualization, and statistical concepts. As you progress, you will implement popular machine learning algorithms for regression, classification, clustering, recommendation systems, anomaly detection, and dimensionality reduction using industry-standard Python libraries.
The course also introduces modern Artificial Intelligence concepts, including deep learning, neural networks, computer vision, and natural language processing (NLP). Through practical coding exercises and real-world projects, you will gain the confidence to build intelligent applications that solve business problems.
In addition to AI and machine learning, you will learn how to leverage Amazon Web Services (AWS) to build scalable, cloud-based AI solutions. You'll understand cloud fundamentals, data storage, model deployment, scalable inference, monitoring, and best practices for deploying machine learning models in production environments.
Throughout the course, you will work on multiple hands-on projects that reinforce every concept and help you build a professional portfolio. By the end of the course, you will have the practical skills needed to analyze data, develop machine learning models, build AI-powered applications, and deploy them on AWS using industry best practices.
Whether your goal is to become a Data Scientist, Machine Learning Engineer, AI Engineer, Python Developer, or Cloud AI Professional, this course provides the practical knowledge and real-world experience needed to succeed in today's AI-driven industry.

Who this course is for

It is for those who want to master Machine Learning and Data Science with Python, NLP and AWS