By the end of this course, learners will be able to build, train, and evaluate machine learning and deep learning models using Python, Scikit-learn, and TensorFlow. They will confidently preprocess datasets, apply classical algorithms, visualize insights, and design neural networks to solve real-world problems.
Master Machine Learning with TensorFlow: Basics to Advanced
您将学到什么
Preprocess datasets, apply classical ML algorithms, and visualize insights in Python.
Build, train, and evaluate machine learning models with Scikit-learn.
Design and implement neural networks with TensorFlow for real-world problems.
您将获得的技能
要了解的详细信息
可分享的证书
添加到您的领英档案
最近已更新！
September 2025
作业
21 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
该课程共有5个模块
This module introduces learners to the foundations of machine learning, its real-world applications, and the tools needed to begin hands-on practice. Students explore what machine learning is, how machines learn, and where ML is applied across industries, setting the stage for practical TensorFlow projects.
涵盖的内容
9个视频4个作业
This module equips learners with essential ML tools such as Anaconda, Jupyter Notebook, and Python libraries. Students learn to manage environments, leverage third-party packages, and perform numerical computations with NumPy for efficient machine learning pipelines.
涵盖的内容
14个视频4个作业
This module focuses on preparing, analyzing, and visualizing data using Pandas, Matplotlib, and Seaborn. Learners handle complex datasets, manage missing values, and create insightful visualizations to uncover patterns, trends, and anomalies essential for ML readiness.
涵盖的内容
38个视频5个作业
This module covers essential preprocessing techniques, data transformation, and classical ML algorithms. Students practice feature engineering, scaling, encoding, and regression modeling while leveraging Scikit-learn to prepare clean and structured datasets.
涵盖的内容
22个视频4个作业
This module introduces deep learning with TensorFlow, covering computational graphs, operations, regression models, and neural networks. Students build and train models using activation functions, optimizers, and the MNIST dataset for hands-on image classification.
涵盖的内容
27个视频4个作业
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状态：免费试用
状态：免费试用Imperial College London
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常见问题
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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