The Machine Learning Internship is a summer bootcamp designed for ages 15-18 and covers the below topics. There are two sessions offered: June 20-July 15 and July 18-August 12, weekdays from 9:00am-10:30am.

Topic 01:
Python (Internals, do’s and don’ts) Architecture, Data Structure
Sub-Topic Installation of Anaconda Prompt Jupyter Notebook-An Overview Shorcut Lkeys in Jupyter Notebook Data Types in Python Rules for Naming the Variables List Tuple Set Dictionary

Topic 02:
Data Analysis , Manipulation with numpy and pandas Python data science package to manipulate, calculate and analyze data
Sub-Topic Machine Learning Libraries Numpy-Hands on Pandas-Hands on

Topic 03:
Exploratory Data Visualization in Python with matplotlib Learn how to explore, visualize, and extract insights from data
Sub-Topic Data Visualization Matplotlib-Hands on Seaborn-Hands on

Topic 04:
Statistical Thinking in Python (Part 1) Build the foundation you need to think statistically and to speak the language of your data
Sub-Topic Measures of Central Tendency Measures of Dispersion IQR Statistics-Hands-On

Topic 05:
Supervised Learning and UnSupervised Learning Classification, Regression, Fine-tuning your model
Sub-Topic Supervised Learning Unsupervised Learning Linear Regression Metrics in Linear Regression Hands-on in Linear Regression

Topic 06:
Logistic regression
Sub-Topic Logistic Regression Metrics in Logistic Regression Hands-on in Logistic Regression

Topic 07:
SVM, Linear Regression
Sub-Topic Support Vector Machine Hands on in SVM

Topic 08:
Preprocessing for Machine Learning in Python Introduction to Data Preprocessing, Standardizing Data
Sub-Topic Exploratory Data Analysis Missing Values Outliers Standardization Mnormalization Feature Scaling and Selection

Topic 09:
Tree Based Models Classification and Regression Trees
Sub-Topic Decision Tree Bagging Boosting Random Forest

To sign up, select the start date for the session you would to attend below. You will receive an email confirmation and the Zoom invitation from the provider.