Build in-demand AI and data skills with hands-on, instructor-led certifications designed for professionals and enterprise teams.
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We deliver fully live sessions led by practitioners who work with AI and data every day.
Our content is shaped around current AI and data science practices used across industries.
We focus on applied learning through real exercises, labs, and problem-solving scenarios.
Our trainers and mentors bring real-world experience, not just academic theory.
We structure programs to help learners build strong fundamentals and progress into applied AI.
Our programs are led by certified instructors with proven industry and academic backgrounds.
I recently took the SAFe for Architects course from Agilefever and found it very helpful in furthering my knowledge of agile architectures and related topics. The comprehensive material covered various topics, including best practices, patterns, and various tools used in modern software development.
I just completed the SAFe Agile Software Engineering 6.0 (ASE) course from Agilefever and can honestly say that it was one of the best courses I have ever taken! It was incredibly informative, providing me with a comprehensive overview of software engineering principles within an agile context.
I have had opportunity to take in Kanban Management Professional training with AgileFever. The trainer was great and helped us with all the questions we had and helped us with the Kanban implementation.
I would recommend AgileFever to anyone who want to take Kanban training with confidence.
I attended the scrum Better with Kanban training with Agile fever – trainer is extremely knowledgeable on Kanban method and provided an excellent walkthrough of the Kanban principles through Handson activities and interactive coaching . I highly recommend taking Kanban trainings at AgileFever.
I attended the Team Kanban Practitioner training with Agile fever – trainer is extremely knowledgeable on Kanban method and provided an excellent walkthrough of the Kanban principles through Handson activities and interactive coaching . I highly recommend taking Kanban trainings at AgileFever.
I have done my TKP with AgileFever and had a great time learning. the trainer was experienced and patiently answered all our questions. At the end of the training, I was confident to go and try Kanban in my teams. I would definitely recommend anyone to choose AgileFever for Kanban training.
Quick answers to help you plan your learning journey better.
To begin, you need a foundation in statistics, programming (often Python), data manipulation, and basic machine learning concepts. Soft skills like problem-solving, analytical thinking, and effective communication also boost your success. Each certification has different prerequisites. Check the course you are interested in.
Yes, many career switchers come from non-tech fields. Your existing domain experience (e.g., finance, marketing, healthcare) often becomes a strength in data roles if paired with solid upskilling in analytics and programming.
Ask yourself: Do you enjoy working with data? Are you willing to learn programming and math basics? Do you like extracting business insights from numbers? These indicators help you gauge readiness.
Time varies by experience, but structured training programs often take 6–12 months to move learners from foundational skills to practical, job-ready competency, especially with hands-on projects.
No, while degrees can help, employers increasingly value skills, projects, and practical outcomes over formal academic credentials. A strong portfolio can often outweigh a specific degree.
Work on projects that solve real problems, predictive models, classification tasks, business insights dashboards, and end-to-end machine learning workflows. Recruiters often look for applied work with clear outcomes.
Data analysts focus on descriptive reporting and dashboards, while data scientists use statistical models, machine learning, and predictive techniques to generate deeper insights and build automated solutions.
Yes, industry-aligned certifications demonstrate your commitment and skills in a structured way, making your profile more credible to recruiters and hiring managers.
Focus on practical skills: explain your projects, demonstrate coding proficiency, and practice problem-solving questions. Employers want to see how you think and apply your knowledge.
Upskilling means building on your current skill set to become more effective in your role; reskilling means learning new skills to move into a different job or field. Both are key to staying relevant in the AI era.
Whether you’re planning to upskill, switch careers, or explore AI & Data Science certifications, our advisors can help you choose the right path.