Getting Started
- Python Programming: Start with the basics of Python, the most popular programming language in data science, and learn how to write efficient code.
- Exploratory Data Analysis (EDA): Discover how to analyze and visualize data to uncover insights and patterns.
- Statistics: Understand the statistical methods that underpin data analysis and machine learning.
- SQL: Learn how to manage and query databases effectively using SQL.
- Machine Learning: Dive into the world of machine learning, covering algorithms, model evaluation, and practical applications.
- Time Series Analysis & Forecasting: Explore techniques for analyzing time-dependent data and making predictions.
- Deep Learning: Get hands-on experience with neural networks and deep learning frameworks.
- Natural Language Processing (NLP): Learn how to process and analyze textual data using NLP techniques.
- Transformers and Generative AI: Understand the latest advancements in AI, including transformer models and generative AI applications.
- Real-World Projects: Apply your skills through engaging projects that simulate real-world data challenges.
In Depth-- https://roadmap.sh/ai-engineer