Create Your Calculator: Learn Python Programming Basics Fast

Description :

Warning: Illegal string offset 'ID' in /home/onlinecou/public_html/wp-content/plugins/advanced-custom-fields-pro/includes/api/api-field.php on line 890

Warning: Illegal string offset 'key' in /home/onlinecou/public_html/wp-content/plugins/advanced-custom-fields-pro/includes/api/api-field.php on line 891

Warning: Illegal string offset 'label' in /home/onlinecou/public_html/wp-content/plugins/advanced-custom-fields-pro/includes/api/api-field.php on line 892

Warning: Illegal string offset 'name' in /home/onlinecou/public_html/wp-content/plugins/advanced-custom-fields-pro/includes/api/api-field.php on line 893

Warning: Illegal string offset 'menu_order' in /home/onlinecou/public_html/wp-content/plugins/advanced-custom-fields-pro/includes/api/api-field.php on line 894

Warning: Illegal string offset 'parent' in /home/onlinecou/public_html/wp-content/plugins/advanced-custom-fields-pro/includes/api/api-field.php on line 895

Warning: Illegal string offset 'key' in /home/onlinecou/public_html/wp-content/plugins/advanced-custom-fields-pro/includes/api/api-field.php on line 899
This is the bite size course to learn Python Programming. You will learn Python Programming very fast and You will create your own calculator very soon after learning the course. You can look into the following courses to get SVBook Certified Data Miner using Python SVBook Certified Data Miner using Python are given to people who have completed the following courses: - Create Your Calculator: Learn Python Programming Basics Fast (Python Basics) - Applied Statistics using Python with Data Processing (Data Understanding and Data Preparation) - Advanced Data Visualizations using Python with Data Processing (Data Understanding and Data Preparation) - Machine Learning with Python (Modeling and Evaluation) and passed a 50 questions Exam. The four courses are created to help learner understand about Python programming basics, then applied statistics (descriptive, inferential, regression analysis) and data visualizations (bar chart, pie chart, boxplot, scatterplot matrix, advanced visualizations with seaborn, and Plotly interactive charts ) with data processing basics to understand more about the the data understanding and data preparation stage of IBM CRISP DM model. Learner will then learn about machine learning and confusion matrix, which is the modeling and evaluation stages of the IBM CRISP DM model. Learner will be able to do data mining project after learning the courses. Content Getting Started Hello World Software Variables and Data Types Data types Conversion Arithmetic Operators Comparison Operators Assignment Operators Boolean Operators Decision Making I (IF statements) Loop (while loop, for loop) Lists Functions Modules Object and Classes Create Your own Calculator