AI & Data Science Development Course
AI & Data Science Development Outline
Foundations of AI & Data Science
- Introduction to AI & Machine Learning
- Data Science Workflow & Methodologies
- Supervised vs. Unsupervised Learning
- Neural Networks & Deep Learning
- AI Ethics & Responsible AI
Data Collection & Preprocessing
- Data Sources (Structured vs. Unstructured)
- Web Scraping & API Integration
- Data Cleaning & Handling Missing Values
- Feature Engineering & Selection
- Data Normalization & Transformation
Exploratory Data Analysis (EDA)
- Data Visualization & Summary Statistics
- Correlation Analysis & Hypothesis Testing
- Outlier Detection & Handling
- Dimensionality Reduction (PCA, t-SNE)
Machine Learning Models
- Supervised Learning
- Linear & Logistic Regression
- Decision Trees & Random Forests
- Support Vector Machines (SVM)
- Gradient Boosting (XGBoost, LightGBM)
- Unsupervised Learning
- Clustering (K-Means, DBSCAN)
- Association Rule Learning (Apriori, FP-Growth)
- Reinforcement Learning
- Markov Decision Processes (MDP)
- Deep Q Networks (DQN)
Deep Learning & Neural Networks
- Artificial Neural Networks (ANN)
- Convolutional Neural Networks (CNN) (for Image Processing)
- Recurrent Neural Networks (RNN) & LSTMs (for Time-Series & NLP)
- Transformer Models (BERT, GPT, T5)
- Autoencoders & GANs (Generative Adversarial Networks)
Natural Language Processing (NLP)
- Text Tokenization & Preprocessing
- Named Entity Recognition (NER)
- Sentiment Analysis & Text Classification
- Text Summarization & Chatbots
- Large Language Models (LLMs) & Prompt Engineering
Computer Vision
- Image Classification & Object Detection
- Image Segmentation & Feature Extraction
- Face Recognition & OCR (Optical Character Recognition)
- Video Processing & Motion Detection
Time-Series Analysis & Forecasting
- ARIMA & SARIMA Models
- Long Short-Term Memory (LSTM) Networks
- Seasonal & Trend-based Forecasting
- Anomaly Detection in Time-Series Data
AI in Business Applications
- AI in Healthcare (Medical Imaging, Disease Prediction)
- AI in Finance (Fraud Detection, Risk Analysis)
- AI in Retail (Customer Insights, Personalization)
- AI in Manufacturing (Predictive Maintenance, Robotics)
- AI in Autonomous Systems (Self-driving Cars, Drones)
Data Engineering & Big Data
- Data Warehousing & ETL Pipelines
- Distributed Computing (Hadoop, Spark)
- Real-time Data Processing (Kafka, Flink)
- Cloud-based AI Solutions (AWS, Azure, GCP)
| Free Seminar Online & Onsite |
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Free Seminar on Feb 3 To 16, 2025
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| Course Start |
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Feb 17, 2025
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