DEEP DIVE INTO DATA SCIENCE : ML- DL- AI

Overview: This program builds on foundational data analytics skills and introduces advanced concepts in machine learning, deep learning, and database management. It also covers data visualization using Power BI and database design principles.

Modules:

1. Power BI

• Create and share interactive dashboards using Power BI.
• Data integration and automation for business reporting.

2. Data Structures and Databases

• Database normalization and SQL for advanced querying.
• Introduction to OLTP and OLAP systems for business analysis.

3. Machine Learning with Python

• Supervised and unsupervised learning techniques.
• Scikit-learn for model implementation, including ensemble algorithms (Random Forest, Gradient Boosting).

4. Deep Learning with Python

• Introduction to neural networks with PyTorch and Keras.
• TensorFlow for model training and deployment.
• Transfer Learning with pre-trained models.

5. Natural Language Processing (NLP):

• Web scraping with Beautiful Soup and Selenium.
• Text processing with NLTK and SpaCy.

Tools:

• Python (Scikit-learn, PyTorch, TensorFlow, Keras, NLTK, SpaCy): For machine learning, deep learning and NLP
• Selenium & Beautiful Soup: For web scraping and data collection.
• Power BI: For data visualization and business reporting.
• SQL (PostgreSQL, MySQL): For database management.

What You’ll Learn:

• Machine Learning: Dive into Scikit-learn for building models and ensemble algorithms for better predictions.
• Deep Learning: Work with PyTorch, Keras, and TensorFlow, including transfer learning and encoder-decoder models.
• Power BI: Advanced dashboard creation and data visualization.
• Database Know-How: Learn about normalization, OLTP, and OLAP systems.

Best For: Those ready to delve into machine learning and deep learning and improve their data handling skills.

Job Prospects:

• Data Scientist: Build and deploy machine learning models to solve complex problems.
• Machine Learning Engineer: Develop and optimize machine learning algorithms and systems.
• Data Engineer: Design and maintain data pipelines and ETL processes.