Artificial Intelligence (AI) Courses

Pandas is a software library written in Python. We can use this library for data analysis and data manipulation that are often needed in machine learning.The Python Pandas Course discusses how to use the Python Pandas library for data analysis, data manipulation, and data visualization in machine learnng.

Seaborn is a data visualization library that is based on matplotlib. Using seaborn we can represent data graphically and get deeper insights into the data. The seaborn using Python course discusses how to visualize data using the Python seaborn library.

Data visualization is the graphical representation of data and we often need it in machine learning. In this data visualization using Python course we have discussed how to represent data graphically for the purpose of machine learning so that we can get deeper insight into the data.

Data preprocessing is a process using which we can process raw data and make the raw data suitable for machine learning models. In this data preprocessing course, we have discussed how to handle missing data, how to encode categorical data, how to discretize continuous values, how to handle outliers in a dataset, how to perform feature scaling, etc.

Scikit-learn or sklearn is a Python library that can be used for solving various machine learning problems. The scikit-learn using Python course discusses how to perform data preprocessing, feature selection, model selection, model evaluation using the Python sklearn library. It also discusses how to solve regression, classification, and clustering problems using the sklearn Python library.

The machine learning using Python course discusses how to use the numpy, pandas, seaborn, matplotlib, sklearn Python libraries for performing various machine learning tasks like data preprocessing, data visualization, feature selection, model selection, model evaluation, etc. The course also discussed how to solve classification, regression or clustering problems using the sklearn Python library.

The Statistics For Machine Learning course discusses various topics of statistics. It also discusses how to solve various statistical problems using Python. This course is good for students and professionals who want to learn statistics for machine learning.

The Linear Algebra course discusses various topics of linear algebra. It also uses Python to solve various problems on this subject. This course is good for students and professionals who want to learn this subject for the purpose of learning cryptanalysis or machine learning.