Data Science is about using capital processes, algorithms, or systems to extract knowledge, insights, and make informed decisions from data.
2. Multivariate Calculus
Most machine learning, invariably data science models, are built with several predictors or unknown variables.
3. Programming, Packages and Softwares
Programming Skills for Data Science brings together all the fundamental skills needed to transform raw data into actionable insights.
4. Data Wrangling
Data Wrangling is the process where you prepare your data for further analysis; transforming and mapping raw data from one form to another to prep up the data for insights.
5. Database Management
Database Management quintessentially consists of a group of programs that can edit, index, and manipulate the database.
6. Data Visualization
Data Visualization is one of the more essential skills because it is not just about representing the final results, but also understand and learn the data and its vulnerability.
7. Machine Learning
Machine Learning for Data Science includes algorithms that are central to ML; K-nearest neighbors, Random Forests, Naive Bayes, Regression Models.
8. Cloud Computing
An everyday role of a Data Scientist generally includes analyzing and visualizing data that are stored in the cloud.