Here are some Python and R basics topics to master: As a beginner, it is recommended that you focus on one language only. Python is widely adopted by industries and academic training programs. You may decide to focus on just one language. Python and R are considered the top programming languages for data science. Gradient Descent Algorithm and its variants (e.g., Stochastic Gradient Descent Algorithm).Here are the topics you need to be familiar with: Most machine learning algorithms perform predictive modeling by minimizing an objective function, thereby learning the weights that must be applied to the testing data in order to obtain the predicted labels. Linear algebra is used in data preprocessing, data transformation, and model evaluation. Linear algebra is the most important math skill in machine learning. Minimum and Maximum values of a function.Step function, Sigmoid function, Logit function, ReLU (Rectified Linear Unit) function.Hence familiarity with multivariable calculus is extremely important for building a machine learning model. Most machine learning models are built with a dataset having several features or predictors. The following list presents essential topics to learn introductory Data Science. Kaggle competitions can be used for capstones, as they provide an opportunity to work on real-world data science projects. Course work has to be accompanied by a capstone project or an internship.
Keep in mind that knowledge acquired from courses alone will not make you a data scientist.
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