Purdue University - No Code AI and Machine Learning Specialization 

PG NC - Program Induction

PG NC - Fundamentals of AI & Machine Learning
Overview of AI & Machine Learning, and Their Importance
Machine Learning Life Cycle
Machine Learning Challenges
Introduction to MLOps
Introduction to No-Code AI & Machine Learning
Advantages and Limitations of No-Code AI & ML
Popular No-Code AI Platforms
Key Features of No-Code AI Platforms
Working with Data in No-Code AI Platforms
Building Models with No-Code Tools

PG NC - Data Collection, Cleaning and Preprocessing
Data Sources and Datasets
Data Acquisition Techniques
Assessing Data Completeness, Consistency, and Accuracy
Automated Data Collection Tools
Data Import and Preprocessing using No-Code Tools
No-Code Tools for Data Transformation
Data Visualization Techniques without Coding
Data Cleaning Techniques using No-Code Platforms
Feature Engineering without Coding
Dimensionality Reduction
Handling Categorical Data
Balancing Imbalanced Datasets
Advanced Imputation Techniques
Advanced Outlier Detection and Treatment
Data Warehousing and ETL Processes

PG NC - Machine Learning Algorithms
Supervised Learning Algorithms
Linear Regression and Polynomial Regression
Using No-Code Tools for Linear Regression
Logistic Regression and Classification Algorithms
Decision Trees, Random Forests and K-Nearest Neighbors
Building Classifiers using No-Code Tools
Unsupervised Learning Algorithms
Clustering Techniques
No-Code Clustering Tools and Visualizations
Dimensionality Reduction Techniques using No-Code Tools
Anomaly Detection and Outlier Analysis
Evaluation Metrics for Regression
Evaluation Metrics for Classification
No-Code Tools for Model Evaluation

PG NC - Advanced ML Techniques & NLP
Ensemble Learning Methods (e.g., Bagging, Boosting)
Support Vector Machines (SVM)
Introduction to Artificial Neural Networks
Building Blocks and Learning Process of ANNs
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Attention Mechanism
Building and Training Neural Network Model with No-Code Tools
Text Analytics and Natural Language Processing (NLP)
Text Processing, Representation, and Sentiment Analysis without Coding
Building NLP Models using No-Code Platforms
Vector Embeddings

PG NC - Model Optimization and Deployment
Cross-Validation Techniques (K-fold, Stratified, etc.)
Model Selection Strategies (Hyperparameter Tuning, Grid Search, Randomized Search, etc.)
Bias-Variance Tradeoff and Overfitting/Underfitting
Feature Selection Techniques without Programming
Model Interpretability and Explainability
Interpreting Model Outputs and Insights
Deploying Models without Coding
Integration with Web and Mobile Applications using No-Code Platforms
Model Monitoring and Management

PG NC - Real-world AI Applications and Case Studies
Applications of No-Code Machine Learning in Various Industries
Case Studies in Finance (Fraud Detection, Credit Scoring)
Case Studies in Healthcare (Diagnosis, Treatment Recommendations)
Case Studies in Marketing (Customer Churn Prediction, Targeted Advertising)
Case Studies on Predictive Analytics
Case Studies on Image Recognition
Common Challenges of No-Code ML
Best Practices for ML Project Success
Ethical Considerations in No-Code ML Deployment

Electives:
PG NC - Academic Masterclass by Purdue University
Attend an online interactive masterclass and get insights about advancements in technology/techniques in No Code Machine Learning.

PG NC - Essentials of Generative AI, Prompt Engineering, and ChatGPT
Cutting-edge knowledge: Learn generative AI, prompt engineering, and ChatGPT
Hands-on skills: Acquire real-world understanding of business applications
Effective GenAI utilization: Master the art of applying Generative AI efficiently
Master prompt engineering: Grasp its significance in producing tailored outputs