Intro to Python
Duration: 3 Weeks
A comprehensive introduction to Python, a fundamental language for Data Science and Machine Learning.
Topics Covered:
- Prep: Data Analysis in Excel & Analytical Problem Solving
- Intro to Python
- Python for DS
Tools and Technologies You'll Master:
SQL and Statistics Essentials
Duration: 3 Weeks
Gain a strong foundation in SQL and key statistical concepts to analyze and interpret data effectively. This course is designed for beginners and professionals looking to enhance their data-handling skills.
Topics Covered:
- SQL queries & database management
- Data retrieval, filtering & aggregation
- Joins & subqueries
- Probability & hypothesis testing
- Descriptive & inferential statistics
- Data visualization techniques
Tools and Technologies You'll Master:
Machine Learning - I
Duration: 3 Weeks
This course introduces the fundamentals of Machine Learning, covering key concepts, algorithms, and practical applications. Learn how to preprocess data, build models, and evaluate performance using industry-standard tools.
Topics Covered:
- Supervised & Unsupervised Learning
- Data Preprocessing & Feature Engineering
- Regression & Classification Algorithms
- Model Evaluation & Optimization
- Basics of Neural Networks
Tools and Technologies You'll Master:
Machine Learning - II
Duration: 3 Weeks
Building on the fundamentals of Machine Learning, this course dives deeper into advanced algorithms, model optimization techniques, and real-world applications. Participants will explore deep learning concepts, ensemble methods, and deployment strategies to enhance their ML skills.
Topics Covered:
- Advanced Supervised & Unsupervised Learning
- Ensemble Methods (Bagging, Boosting, Random Forest)
- Dimensionality Reduction Techniques (PCA, t-SNE)
- Deep Learning Fundamentals (Neural Networks, CNNs)
- Hyperparameter Tuning & Model Optimization
- Model Deployment & Productionization
Tools and Technologies You'll Master:
Deep Learning
Duration: 3 Weeks
This course provides a comprehensive understanding of deep learning, covering neural networks, optimization techniques, and real-world applications. Learn how to build and train deep learning models for tasks like image recognition and sequence prediction.
Topics Covered:
- Introduction to Deep Learning & Neural Networks
- Backpropagation & Optimization Techniques
- Convolutional Neural Networks (CNNs) for Image Processing
- Recurrent Neural Networks (RNNs) & LSTMs for Sequential Data
- Transfer Learning & Pretrained Models
- Model Deployment & Performance Optimization
Tools and Technologies You'll Master:
Natural Language Processing
Duration: 3 Weeks
This course explores the fundamentals of NLP, enabling you to build intelligent systems that understand, analyze, and generate human language. Learn key NLP techniques, including text preprocessing, sentiment analysis, and transformer-based models.
Topics Covered:
- Text Preprocessing & Tokenization
- Word Embeddings (Word2Vec, GloVe)
- Named Entity Recognition (NER)
- Sentiment Analysis & Text Classification
- Sequence Modeling with RNNs & LSTMs
- Transformer Models (BERT, GPT)
Tools and Technologies You'll Master:
U.S Nationals
Foreign Nationals