Python in 2021

As you will progress in the Data Science with Python training program, you will get to know the below thingsStatistics for data scienceBasic data cleaning techniques for model buildingConverting your raw data into a machine consumable formatWorking principle of machine learning models and their applicabilityUnderstanding the parameters required for checking model accuracyDeploying the model to make it available as a serviceMaintaining the model over a period of timeWith respect to the above steps, you will also learn how to use data science specific libraries in Python eg. Frequently used libraries in data cleaning like NumPy, pandas, spicy, groupby, merge; data plotting libraries like matplotlib, seaborn; machine learning-based modules available inside scikit learn for building various regression and classification based algorithms, libraries to check model accuracy like confusion matrix, MSE, RMSE, Natural Language-based libraries like NLTK, genism, VADER. These will help learners with applied data science with python