Certified AI Engineering Masterclass: From Zero to AI Hero
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Week 1 Python Programming BasicsIntroduction to Week 1 Python Programming Basics0sDay 1 Introduction to Python and Development Setup0sDay 2: Control Flow in Python0sDay 3: Functions and Modules0sDay 4: Data Structures (Lists, Tuples, Dictionaries, Sets)0sDay 5: Working with Strings0sDay 6: File Handling0sDay 7: Pythonic Code and Project Work0s
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Week 2 Data Science EssentialsIntroduction to Week 2 Data Science Essentials0sDay 1: Introduction to NumPy for Numerical Computing0sDay 2: Advanced NumPy Operations0sDay 3: Introduction to Pandas for Data Manipulation0sDay 4: Data Cleaning and Preparation with Pandas0sDay 5: Data Aggregation and Grouping in Pandas0sDay 6: Data Visualization with Matplotlib and Seaborn0sDay 7: Exploratory Data Analysis (EDA) Project0s
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Week 3 Mathematics for Machine LearningIntroduction to Week 3 Mathematics for Machine Learning0sDay 1: Linear Algebra Fundamentals0sDay 2: Advanced Linear Algebra Concepts0sDay 3: Calculus for Machine Learning (Derivatives)0sDay 4: Calculus for Machine Learning (Integrals and Optimization)0sDay 5: Probability Theory and Distributions0sDay 6: Statistics Fundamentals0sDay 7: Math-Driven Mini Project – Linear Regression from Scratch0s
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Week 4 Probability and Statistics for Machine LearningIntroduction to Week 4 Probability and Statistics for Machine Learning0sDay 1: Probability Theory and Random Variables0sDay 2: Probability Distributions in Machine Learning0sDay 3: Statistical Inference – Estimation and Confidence Intervals0sDay 4: Hypothesis Testing and P-Values0sDay 5: Types of Hypothesis Tests0sDay 6: Correlation and Regression Analysis0sDay 7: Statistical Analysis Project – Analyzing Real-World Data0s
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Week 5 Introduction to Machine LearningIntroduction to Week 5 Introduction to Machine Learning0sDay 1: Machine Learning Basics and Terminology0sDay 2: Introduction to Supervised Learning and Regression Models0sDay 3: Advanced Regression Models – Polynomial Regression and Regularization0sDay 4: Introduction to Classification and Logistic Regression0sDay 5: Model Evaluation and Cross-Validation0sDay 6: k-Nearest Neighbors (k-NN) Algorithm0sDay 7: Supervised Learning Mini Project0s
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Week 6 Feature Engineering and Model EvaluationIntroduction to Week 6 Feature Engineering and Model Evaluation0sDay 1: Introduction to Feature Engineering0sDay 2: Data Scaling and Normalization0sDay 3: Encoding Categorical Variables0sDay 4: Feature Selection Techniques0sDay 5: Creating and Transforming Features0sDay 6: Model Evaluation Techniques0sDay 7: Cross-Validation and Hyperparameter Tuning0s
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Week 7 Advanced Machine Learning AlgorithmsIntroduction to Week 7 Advanced Machine Learning Algorithms0sDay 1: Introduction to Ensemble Learning0sDay 2: Bagging and Random Forests0sDay 3: Boosting and Gradient Boosting0sDay 4: Introduction to XGBoost0sDay 5: LightGBM and CatBoost0sDay 6: Handling Imbalanced Data0sDay 7: Ensemble Learning Project – Comparing Models on a Real Dataset0s
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Week 8 Model Tuning and OptimizationIntroduction to Week 8 Model Tuning and Optimization0sDay 1: Introduction to Hyperparameter Tuning0sDay 2: Grid Search and Random Search0sDay 3: Advanced Hyperparameter Tuning with Bayesian Optimization0sDay 4: Regularization Techniques for Model Optimization0sDay 5: Cross-Validation and Model Evaluation Techniques0sDay 6: Automated Hyperparameter Tuning with GridSearchCV and RandomizedSearchCV0sDay 7: Optimization Project – Building and Tuning a Final Model0s
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Week 9 Neural Networks and Deep Learning FundamentalsIntroduction to Week 9 Neural Networks and Deep Learning Fundamentals0sDay 1: Introduction to Deep Learning and Neural Networks0sDay 2: Forward Propagation and Activation Functions0sDay 3: Loss Functions and Backpropagation0sDay 4: Gradient Descent and Optimization Techniques0sDay 5: Building Neural Networks with TensorFlow and Keras0sDay 6: Building Neural Networks with PyTorch0sDay 7: Neural Network Project – Image Classification on CIFAR-100s
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Week 10 Convolutional Neural Networks CNNsIntroduction to Week 10 Convolutional Neural Networks (CNNs)0sDay 1: Introduction to Convolutional Neural Networks0sDay 2: Convolutional Layers and Filters0sDay 3: Pooling Layers and Dimensionality Reduction0sDay 4: Building CNN Architectures with Keras and TensorFlow0sDay 5: Building CNN Architectures with PyTorch0sDay 6: Regularization and Data Augmentation for CNNs0sDay 7: CNN Project – Image Classification on Fashion MNIST or CIFAR-100s
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Week 11 Recurrent Neural Networks RNNs and Sequence ModelingIntroduction to Week 11 Recurrent Neural Networks (RNNs) and Sequence Modeling0sDay 1: Introduction to Sequence Modeling and RNNs0sDay 2: Understanding RNN Architecture and Backpropagation Through Time (BPTT)0sDay 3: Long Short-Term Memory (LSTM) Networks0sDay 4: Gated Recurrent Units (GRUs)0sDay 5: Text Preprocessing and Word Embeddings for RNNs0sDay 6: Sequence-to-Sequence Models and Applications0sDay 7: RNN Project – Text Generation or Sentiment Analysis0s
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Week 12 Transformers and Attention MechanismsIntroduction to Week 12 Transformers and Attention Mechanisms0sDay 1: Introduction to Attention Mechanisms0sDay 2: Introduction to Transformers Architecture0sDay 3: Self-Attention and Multi-Head Attention in Transformers0sDay 4: Positional Encoding and Feed-Forward Networks0sDay 5: Hands-On with Pre-Trained Transformers – BERT and GPT0sDay 6: Advanced Transformers – BERT Variants and GPT-30sDay 7: Transformer Project – Text Summarization or Translation0s
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Week 13 Transfer Learning and FineTuningIntroduction to Week 13 Transfer Learning and Fine-Tuning0sDay 1: Introduction to Transfer Learning0sDay 2: Transfer Learning in Computer Vision0sDay 3: Fine-Tuning Techniques in Computer Vision0sDay 4: Transfer Learning in NLP0sDay 5: Fine-Tuning Techniques in NLP0sDay 6: Domain Adaptation and Transfer Learning Challenges0sDay 7: Transfer Learning Project – Fine-Tuning for a Custom Task0s
Welcome to the AI Engineering Masterclass: From Zero to AI Hero! This comprehensive AI course is designed to take you on an exciting journey from an AI beginner to a confident AI Engineer, equipped with the skills to build, train, and deploy Artificial Intelligence solutions. Whether you’re starting from scratch or looking to solidify your AI expertise, this AI Masterclass provides the step-by-step roadmap you need to succeed.
In this AI Engineering Masterclass, you’ll begin with the foundations of AI, exploring Python programming, data preprocessing, and the basics of machine learning. As you progress, you’ll dive into advanced AI topics such as neural networks, deep learning, natural language processing (NLP), and computer vision. You’ll also gain hands-on experience with cutting-edge AI frameworks like TensorFlow, PyTorch, and Hugging Face to create production-ready AI solutions.
This AI Masterclass emphasizes practical AI skills, with real-world projects embedded into every module. You’ll learn to tackle real business problems using AI technologies, optimize AI models, and deploy scalable solutions.
Why Choose the AI Engineering Masterclass?
Beginner-Friendly AI Curriculum: Start from scratch and grow into an expert
Hands-On AI Projects: Build real AI applications for real-world challenges
Master AI Frameworks: Learn TensorFlow, PyTorch, and Hugging Face
Comprehensive AI Training: Cover Python, Machine Learning, Deep Learning, NLP, and AI Deployment
Zero to AI Hero Roadmap: Structured learning path for complete AI mastery
By the end of this AI Engineering Masterclass, you’ll not only have mastered AI engineering skills, but you’ll also be equipped to innovate, lead AI projects, and drive transformation with AI solutions in your organization or startup.
Whether you’re an aspiring AI Engineer, an AI enthusiast, or someone looking to break into the Artificial Intelligence industry, this AI Masterclass is your ultimate resource to go From Zero to AI Hero.
Join the AI Revolution Today – Enroll in the AI Engineering Masterclass: From Zero to AI Hero and take the first step towards mastering AI!
What's included
- 31 hours on-demand video
- 1 article
- 2 downloadable resources
- Access on mobile and TV
- Certificate of completion