Location

Community Services & Continuing Education - Alexandria

Objectives

• Learn required skills such as statistical analysis, Python, machine learning, data analysis and more to work as a data scientist.

Outcomes

By the end of this course, students will be able to:• Deal with the programming language required in the field of AI.• Work as a data scientist.• Analyze data and statistical analyzes using the Python language.• Build a machine learning model.

Course Contents

1- Statistical 1-1 Descriptive Statistical 1-2 Inferential Statistical 2- Mathematics for AI 2-1 Calculus 2-2 Linear algebra 3- Programming – Python3-1 Data type3-2 Functions3-3 lambda Expression3-4 Numby3-4 Panda3-5 matplot4- Machine learning4-1 Supervised Learning 4-1-1 Regression Simple Linear Regression Multiple Linear Regression Other Regression Methods 4-1-2 Classification Logistic Regression SVM4-2 Unsupervised Learning 4-2-1 Clustering K-Means 4-2-2 Dimension Reduction PCA4-3 Model Selection & Evaluation  Cross Validation5- Data Analytics 5-1- Introduction to Data Analysis 5-2- Data analysis process with python 5-3-Data Visualization with python 5-4- introduction of Power BI and Tableau