DATA SCIENCE
Data science is a multidisciplinary field that combines statistics, computer science, and domain expertise to extract insights and knowledge from data. It involves various processes, including data collection, cleaning, analysis, and visualization. Key components of data science include:

Data Collection: Gathering data from various sources, such as databases, APIs, or web scraping.

Data Cleaning: Preparing the data for analysis by removing errors, handling missing values, and ensuring consistency.

Exploratory Data Analysis (EDA): Analyzing the data to discover patterns, trends, and relationships through visualization and summary statistics.

Modeling: Applying statistical and machine learning techniques to make predictions or classify data.

Evaluation: Assessing the performance of models using metrics like accuracy, precision, and recall.

Deployment: Implementing models in real-world applications, often through APIs or integrated software solutions.
https://www.sevenmentor.com/da....ta-science-course-in

FULL STACK
Training programs typically range from a few weeks to several months, depending on the thoroughness of the curriculum. A well-structured training program will include:

Lectures and Tutorials: These will give you the foundational knowledge you need.

Hands-on Projects: You'll be expected to work on real-world projects, simulating what you might encounter in a job.

Peer Collaboration: Many classes encourage group projects, which helps in understanding teamwork and improves problem-solving skills.

Skills Development

During your training, you’ll likely be taught crucial skills such as:

Version control systems like Git

Database management

APIs and RESTful services

Responsive design principles

Discovering areas you enjoy (or even ones you don’t) can guide your career path. For instance, while you might initially be drawn to design, you may find that back-end logic fascinates you more.
https://www.sevenmentor.com/fu....ll-stack-training-in