Artificial Intelligence Journey: Beginner to Pro
Data Science Academy
AI Engineering Bootcamp
This course is popular
6 people enrolled last week.
Build Real AI Applications with Python, Machine Learning & Deep Learning
Artificial Intelligence is transforming every industry — from healthcare and finance to transportation, retail, and cybersecurity. Yet many professionals struggle to move beyond theory and actually build real AI systems.
This course is designed to solve that problem.
Instead of focusing only on concepts, this program walks you through the complete journey of building practical AI solutions. You will start with the foundations of Artificial Intelligence and Python for data science, then progressively learn how to design machine learning models, evaluate them properly, and build deep learning systems.
Along the way, you will implement real projects such as housing price prediction, sentiment analysis, image classification with neural networks, and AI-powered web applications.
By the end of the course, you will not only understand how AI works — you will know how to build, test, and deploy AI models into real applications using modern tools like Python, TensorFlow, PyTorch, and Streamlit.
You will leave with practical skills, portfolio-ready projects, and the confidence to build your own AI-powered applications.
What you’ll learn
Go from AI beginner to building real ML and deep learning applications ready for deployment.
Train regression, classification, and clustering models using real datasets.
Use Python, NumPy, Pandas, and Scikit-learn to build ML pipelines.
Evaluate models using accuracy, precision, recall, and confusion matrices.
Understand perceptrons, activation functions, and backpropagation.
Build deep learning models using TensorFlow and PyTorch.
Train models on datasets like MNIST for real-world applications.
Preprocess text using tokenization, stopwords, and TF-IDF.
Build sentiment analysis models using Logistic Regression and Naïve Bayes
Understand embeddings and transformer-based models.
Understand image data, filters, and augmentation techniques.
Design CNN architectures for image classification tasks.
Implement transfer learning using pretrained models.
Learn reinforcement learning fundamentals like agents and rewards.
Explore generative AI including diffusion models and GPT systems.
Apply responsible AI principles and bias mitigation
Build AI web apps using Flask and Streamlit.
Deploy models on cloud platforms like AWS, Azure, or Google Cloud.
Understand CI/CD, monitoring, and MLOps fundamentals.
Learn directly from Data
Data Science Academy
AI engineers building practical machine learning and deep learning systems.
Who this course is for
Developers or engineers who want to transition into AI and build real machine learning and deep learning applications.
Data analysts and tech professionals looking to expand their skills into AI, ML, NLP, and computer vision.
Students and beginners interested in learning AI from fundamentals to real-world projects and deployment.
What's included
Live sessions
Learn directly from Data Science Academy in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
Week 1
Day 1 - Introduction to Artificial Intelligence
Day 2 - Python Foundations for AI
Day 3 - Machine Learning Essentials
Day 4 - Deep Learning & Neural Networks
Day 5 - Natural Language Processing (NLP)
Day 6 - Computer Vision
Day 7 - Advanced AI Topics
Week 2
Day 8 - AI Project Deployment
Schedule
Live sessions
2 hrs / week
Projects
8 hrs / week
Async content
10 hrs / week
Frequently asked questions
$200
USD
2 days left to enroll