This course teaches you the essential skills required to process and prepare data, model, and evaluate machine learning models. Data processing is a fundamental step in extracting valuable insights from raw data and is crucial in professional data science and machine learning careers.
In this section, we cover essential data transformation, enrichment, and cleaning techniques, including encoding, normalization, joining, and handling data quality issues to prepare datasets for robust analytics and machine learning applications.
涵盖的内容
1个视频8篇阅读材料1个作业
显示有关单元内容的信息
1个视频•总计1分钟
Data Processing and Preparation - Overview Video•1分钟
8篇阅读材料•总计100分钟
Introduction•15分钟
Transformation Functions•15分钟
Pivoting•15分钟
Joins•15分钟
Data Cleaning•10分钟
Addressing Duplicate Data•10分钟
Handling Class Imbalance•10分钟
Exam Essentials•10分钟
1个作业•总计10分钟
Data Processing Fundamentals•10分钟
Modeling and Evaluation
第 2 单元•小时 后完成
单元详情
In this section, we construct and evaluate predictive models using regressors, classifiers, and temporal methods, assess performance with metrics like RMSE and F1 score, and explore concepts such as bias-variance trade-off and hyperparameter tuning.
涵盖的内容
1个视频8篇阅读材料1个作业
显示有关单元内容的信息
1个视频•总计1分钟
Modeling and Evaluation - Overview Video•1分钟
8篇阅读材料•总计85分钟
Introduction•10分钟
The Challenge of Censoring in Survival Analysis•10分钟
Model Design Concepts•10分钟
The Law of Parsimony (Occam's Razor)•10分钟
Model Evaluation•10分钟
Accuracy•15分钟
Real World Scenario - Choosing the Appropriate Performance Metric•10分钟
Exam Essentials•10分钟
1个作业•总计10分钟
Evaluating Machine Learning Models•10分钟
Model Validation and Deployment
第 3 单元•小时 后完成
单元详情
In this section, we evaluate model performance using key metrics and constraints, compare deployment strategies including MLOps, and discuss effective communication of model outcomes to stakeholders for practical data science applications.
涵盖的内容
1个视频7篇阅读材料1个作业
显示有关单元内容的信息
1个视频•总计1分钟
Model Validation and Deployment - Overview Video•1分钟
7篇阅读材料•总计70分钟
Introduction•10分钟
Real World Scenario - Developing a Product Recommendation Model•10分钟
Residual Plot•10分钟
Real World Scenario•10分钟
Cloud Deployment•10分钟
Machine Learning Operations (MLOps)•10分钟
Testing•10分钟
1个作业•总计10分钟
Model Validation and Deployment Fundamentals•10分钟
Unsupervised Machine Learning
第 4 单元•小时 后完成
单元详情
In this section, we explore association rules, focusing on their structure, interpretation of itemsets, antecedents, and consequents, and how actionable patterns in transactional data inform data-driven decisions.
We embrace the potential in data and technology. Whether it’s equipping researchers with powerful insights that fuel their work or inspiring our community of learners to drive change in their fields. We’re committed to fast-tracking innovation, unlocking new possibilities, and championing breakthroughs that redefine industries and improve lives.
With a legacy built on trust, our 200 years of experience in publishing allows us to be your partner in shaping a world driven by information, curiosity, and continuous advancement.
When will I have access to the lectures and assignments?
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.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
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.