该课程采用由浅入深、项目驱动的教学方式，旨在帮助学员掌握从数据处理到AI模型云端部署的全流程技能。
基础与数据分析：从零开始学习Python编程，精通NumPy、Pandas、Matplotlib等核心库，掌握统计学、EDA（探索性数据分析）和特征工程，打牢数据处理基本功。
核心机器学习：深入理解监督与无监督学习算法（如经典回归、分类和聚类），学习如何评估、调优并构建工业级预测模型。
深度学习与NLP前沿：依托TensorFlow、PyTorch等主流框架，从基础神经网络（ANN）跨越到现代主流架构（CNN、RNN、LSTM、Transformer），全面攻克文本分词、情感分析、机器翻译和对话系统等自然语言处理高级技术。
云端部署与工程落地：跳出单纯的本地代码编写，聚焦AI模型的工程化能力，传授如何利用AWS云服务进行模型托管、API发布和部署，打造真正可投入生产的端到端AI应用。
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 484.46 MB | Duration: 0h 55m
Master Machine Learning, Data Science from beginner to Advanced with Python, NLP, AWS and Hands-on Projects
What you’ll learn
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
Deploy AI and Machine Learning models on AWS by learning cloud-based ML services, model deployment
Requirements
No need to have any experience at all
Description
Master the complete Artificial Intelligence ecosystem with this comprehensive, hands-on course covering Machine Learning, Data Science, Deep Learning, Natural Language Processing (NLP), and AI using Python. Designed for beginners, students, software developers, data analysts, and aspiring AI engineers, this course takes you from the fundamentals to advanced AI concepts through practical coding exercises and real-world projects.You will start by learning Python programming for data science, followed by essential topics such as data preprocessing, exploratory data analysis (EDA), feature engineering, data visualization, statistics, and probability. You’ll then dive into machine learning, where you’ll build predictive models using supervised and unsupervised learning algorithms, evaluate model performance, and optimize models using industry best practices.As you progress, you’ll explore the exciting world of Deep Learning by building artificial neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), LSTMs, transformers, and modern deep learning architectures using popular frameworks such as TensorFlow, Keras, and PyTorch.The course also provides an in-depth introduction to Natural Language Processing (NLP), where you’ll learn text preprocessing, tokenization, word embeddings, sentiment analysis, text classification, named entity recognition, question answering, document summarization, machine translation, and conversational AI. You’ll also discover how Large Language Models (LLMs) and Generative AI are transforming modern AI applications.Throughout the course, you will develop numerous real-world projects involving predictive analytics, recommendation systems, fraud detection, image classification, object detection, text analytics, chatbots, and AI-powered automation. These projects are designed to strengthen your practical skills and help you build a professional portfolio.By the end of this course, you will be able to collect and analyze data, build machine learning models, design deep learning solutions, create NLP applications, and develop intelligent AI systems using Python. Whether you aspire to become a Data Scientist, Machine Learning Engineer, AI Engineer, Deep Learning Engineer, NLP Engineer, or Python Developer, this course will provide the practical knowledge and hands-on experience needed to excel in the rapidly growing field of Artificial Intelligence.
It is for those who want to master Machine Learning and Data Science with Python, NLP and AWS
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