AI Engineer Career Track

Ready to launch your career in one of today's fastest-growing roles? Follow our structured AI Engineer Career Track to master the skills to build and deploy AI solutions—from foundations to advanced AI tools.

10 Career Track Courses
33 Hours of Video
Certificate of Achievement
Start Your Career
AI Engineer

AI Engineer Career Track Courses

Want to know how to become an AI engineer? Our structured AI engineer roadmap helps you gain the skills you need for a successful career in artificial intelligence.

What's an AI Engineer Career Track? It’s a curated AI curriculum offering a structured, step-by-step learning path through essential courses—from programming and data management to advanced AI techniques.

Our AI engineer training program combines theoretical foundations with hands-on practice, preparing you for real-world AI development challenges. Master machine learning fundamentals, neural network architectures, and popular AI tools while building practical projects.

This AI engineer roadmap culminates in a professional AI Engineer certificate that validates your expertise and establishes you as a certified AI engineer.

Learn AI from industry experts and get certified for your AI engineering career through our comprehensive AI curriculum.
Intro to AI
Optional

Intro to AI

with Ned Krastev
4.8/5
(737)

This AI fundamentals course is the perfect introduction to the field. Gain an overall understanding of AI and learn the intuition behind today's state of the art artificial intelligence models

2 hours of content
1
Introduction to Python
Required

Introduction to Python

with Martin Ganchev
4.8/5
(4,748)

Learn to code in Python: the most popular and widely used programming language

2 hours of content
2
Data Cleaning and Preprocessing with pandas
Required

Data Cleaning and Preprocessing with pandas

with Martin Ganchev
4.7/5
(1,759)

Master Python’s quintessential pandas library and its core data structures – Series and DataFrame objects. Elevate your data analysis skills for real-world challenges

3 hours of content
3
Intro to NLP for AI
Required

Intro to NLP for AI

with Lauren Newbould
4.7/5
(449)

Master Natural Language Processing: Leverage Python and Machine Learning to build effective NLP systems

3 hours of content
4
Intro to LLMs
Required

Intro to LLMs

with Lauren Newbould
4.7/5
(315)

Start your AI Engineer career journey: Master Transformer Architecture and the Essentials of Modern AI

3 hours of content
5
Build Chat Applications with OpenAI and LangChain
Required

Build Chat Applications with OpenAI and LangChain

with Hristina Hristova
4.8/5
(177)

Gain cutting-edge AI skills: Master the LangChain framework to build and deploy real-world AI applications

9 hours of content
6
Introduction to Vector Databases with Pinecone
Required

Introduction to Vector Databases with Pinecone

with Elitsa Kaloyanova
4.8/5
(121)

Gaining insights from data is crucial for businesses. With emerging AI technologies, the importance of vectorization and vector databases is set to increase significantly. In this Vector Databases with Pinecone course, you’ll have the opportunity to explore the Pinecone database—a leading vector solution—and learn to implement a vector database for semantic search using real data.

2 hours of content
7
LLM Engineering in Practice with Streamlit and OpenAI
Required

LLM Engineering in Practice with Streamlit and OpenAI

with Petar Petrov
4.7/5
(39)

Dive into the world of AI solutions with this hands-on course. Learn how to design, develop, and deploy an interview simulator project using Streamlit, integrating language models, feedback systems, and advanced prompts. Master key concepts in AI, prompt engineering, and app development while solving real-world challenges.

4 hours of content
8
Speech Recognition with Python
Elective

Speech Recognition with Python

with Ivan Manov
4.8/5
(21)

Master speech recognition—the technology that enables machines to understand human speech by converting voice into readable data. Utilize Python speech recognition tools to transcribe audio to text with cutting-edge AI models.

3 hours of content
9
ChatGPT for Data Science
Elective

ChatGPT for Data Science

with Elitsa Kaloyanova
4.8/5
(246)

Boost your productivity with ChatGPT Advanced Data Analysis: Solve data science problems with ChatGPT

2 hours of content
10

FAQs

Need help finding what you're looking for? Visit the 365 Data Science Help Center page or contact us directly.

What do I need to start as an AI engineer?

To begin your AI engineer career path, you'll need:

  • Basic programming knowledge
  • Understanding of mathematics and statistics
  • Commitment to learning AI tools and frameworks
  • Willingness to complete hands-on AI projects

Our AI Engineer Career Track certificate covers machine learning and neural network certification programs—providing you with the credentials you need to excel in AI development.

Is AI engineering a good career?

AI engineering is a gratifying career featuring:

  • High demand, with 97 million new AI-related jobs expected by 2025
  • An average annual AI engineer salary over $200,000 for US
  • Engagement with cutting-edge technologies like TensorFlow, PyTorch, and GPT models
  • Frequent interaction with emerging AI tools
  • Ongoing advancement through specializations in machine learning, deep learning, and neural network

Ready to start your journey? Enroll in our AI Engineer Career Track today and take the first step toward becoming a certified AI engineer.

How long does it take to become an AI engineer?

The journey to becoming an AI engineer varies based on your background and dedication. Our AI engineer training program can take you from beginner to AI engineer in 1 to 2 years. It includes:

  • Core AI training and machine learning certification (3-6 months)
  • Practical project work with AI tools and frameworks (3-6 months)
  • Advanced specialization in neural networks and deep learning (3-6 months)

Start the AI Engineer Career Track now to begin your career journey.

What is the career path to become an AI engineer?

The AI engineer career path typically involves:

  • Completing fundamental programming and mathematics training
  • Pursuing specialized AI engineering courses and certification
  • Building practical experience through hands-on AI projects
  • Developing expertise in machine learning and neural network applications

Our AI Engineer Career Track comprehensively covers all these essential steps—offering structured learning paths, hands-on projects, and expert guidance to help you master each component of the AI engineering journey.

What is the growth path for an AI engineer?

Wondering how to become an AI engineer and where the role can take you? AI engineers can advance through several career stages:

  • Junior AI Engineer: Focus on implementing AI solutions.
  • Senior AI Engineer: Lead complex AI projects and mentor others.
  • AI Architect: Design large-scale AI systems.
  • AI Research Scientist: Drive innovation in artificial intelligence.

Our AI engineer training equips you with advanced skills and practical experience to accelerate your AI engineer job growth.

Are AI engineer jobs in demand?

The demand for AI engineer jobs is exceptionally high.

With an estimated 97 million new AI-related jobs projected by 2025, the field presents unprecedented opportunities for skilled professionals. Companies across sectors actively recruit professionals with AI certification and machine learning expertise.

This trend will continue as AI technology becomes more prevalent in business operations.

Learn AI and launch your career with our AI Engineer Career Track.

How difficult is it to become an AI engineer?

Becoming an AI engineer requires strong technical skills, dedication to continuous learning, and experience with machine learning frameworks.

The difficulty level varies depending on your background; those with programming and mathematics experience may find it easier to adapt. But with consistent effort and the proper AI engineer roadmap, it's an achievable goal for those committed to the field.

Our structured AI engineer courses and AI engineer certification make this journey more manageable by providing comprehensive AI curriculum support, hands-on projects, and expert guidance throughout your learning process.

AI Engineer Career Track

10 Courses

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