Generative AI Skills for Data Scientists
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Course
Generative AI Skills for Data Scientists
Build the next generation of data solutions with generative AI. Master data creation, feature engineering, and model implementation and stay ahead of the curve.
Flexible Schedule
Intermediate Level
Mentor Support
Duration
Generative AI is transforming the way data professionals solve problems and create insights. This course introduces how data scientists use generative AI for data generation, augmentation, and feature engineering across real-world applications.
In this course, youll explore how generative AI speeds up visualization, model building, and data-driven decision-making. Youll also examine key ethical considerations around AI and data handling that are shaping business practices across industries.
Through hands-on labs and a guided project, youll apply generative AI techniques to practical data science scenarios. By the end, youll have a portfolio-ready project and certificate that demonstrate your expertise in applying GenAI to data science.
This course comprises three purposely designed modules that take you on a carefully defined learning journey.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules. It is anticipated that you will complete the course in 11 hours. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And dont worry, youre not alone! You will be encouraged to stay connected with your learning community through the course discussion space.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include discussion space, videos, reading material, quizzes, hands-on labs, quizzes and final assignment.
Once you have successfully completed the course, you will earn your IBM Certificate.
By the end of this course, you will be able to:
- Implement generative AI for data generation and augmentation.
- Apply AI and LLM techniques for feature engineering.
- Use generative AI to enhance data visualization and insights.
- Solve real-world data science problems using AI-driven models.
- Apply ethical and responsible AI principles in data science.
- Aspiring and current data scientists.
- Data professionals and analysts seeking generative AI expertise.
- Engineers and technical learners exploring GenAI for data workflows.
- Basic understanding of data science workflows
Course Outline
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
This course equips learners with essential generative AI for data scientists by focusing on data generation, augmentation, feature engineering, model implementation, and visualization. It also explores ethics in generative AI and how it applies to solving real-world data science problems.
The course is designed for aspiring and professional data scientists, analysts, engineers, and data professionals who want to strengthen their expertise in generative AI in data science.
Generative AI in data science enables the creation of synthetic datasets, improves data balance, and strengthens model performance. Learners gain hands-on experience with data augmentation techniques to address real-world challenges.
Yes, the course teaches how to apply generative AI for feature engineering, model building, and practical implementationskills highly relevant for any generative AI data scientist.
Generative AI for data scientists enhances visualization by accelerating the discovery of patterns and generating insights faster. Learners explore AI-powered visualization techniques to extract value from data.
Yes, youll complete a hands-on project focused on feature engineering and data augmentation. This portfolio-ready work demonstrates your generative AI data science skills to employers.
Absolutely. The course includes a project that allows learners to apply data generation, augmentation, and feature engineering with generative AI for data scientists.
Through practical exercises and projects, youll see how generative AI addresses issues like imbalanced data, limited datasets, visualization bottlenecks, and extracting insights across industries.
Generative AI in data science has applications in healthcare, finance, retail, marketing, and technologyindustries where data-driven decisions require better models and insights.
Yes, the curriculum covers ethics and responsible AI practices, helping learners understand the risks of generative AI and data while developing solutions that align with industry standards.
No advanced prerequisites are required, but familiarity with basic AI for data science concepts is helpful. The course is suitable for beginners and professionals alike.
Generative AI for data scientists is one of the most in-demand skills. By completing this training, youll strengthen your expertise and position yourself as a generative AI data scientist ready for new opportunities.
Yes, youll earn an IBM Certificate after completing the project and final quiz. This Generative AI for Data Scientists credential can be shared with employers to showcase your expertise.
A generative AI data scientist is a professional skilled in applying generative AI models and techniquessuch as data augmentation, visualization, and model implementationto solve data science challenges across industries.
While salaries vary by location and experience, professionals with generative AI skills for data scientists often command higher pay due to the demand for expertise in data science with generative AI course certifications.
Type of certificate
IBM Certificate
About this course
03 Modules
05 Skills
Includes
Discussion space
09 Hands-on labs
04 Practice quizzes
02 Graded quizzes
01 Final project
01 Final exam
Create
Model development
Exercises to explore
Simple generative tool
Data generation, augmentation and preparation
Querying databases
Data insights & visualization
This course has been created by
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