Learning Resources

Welcome to the Learning Resources tab—your gateway to knowledge, growth, and the occasional “Wait… I swear it worked yesterday!” moment. Before you dive into the deep end of learning, grab your coffee, take a deep breath, and prepare to level up your skills. 📚

YouTube Videos 📺

These videos provide a solid foundation in key mathematical and programming concepts essential for data science. Whether you’re brushing up on Python, R, linear algebra, or probability, these resources will help reinforce your understanding through visual and practical examples.

#### Learn Python

#### Learn R

#### Learn Linear Algebra

#### Learn Calculus

#### Learn Probability

#### Learn Statistics

Online Platforms & Certifications 🌐

These platforms offer interactive courses and certifications that will enhance your data science skills. Earning certifications from AWS or Microsoft can also help validate your expertise in cloud computing and machine learning for future employers.

Codecademy

Coursera

edX

Udacity

AWS Certifications

Microsoft Certifications

Online Books 📚

These books provide in-depth theoretical knowledge and practical applications in essential areas of data science. They cover topics such as statistics, machine learning, deep learning, and data mining to help you build a strong foundation in analytical techniques.

Learn Linear Algebra

• Linear Algebra for Everyone

Learn Calculus

• Stewart, J. (2012). Calculus: Early Transcendentals (7th ed.). Brooks Cole.

Learn Statistics

• OpenStax. (n.d.). Introductory Statistics. OpenStax.

Learn Probability

• Piech, C. (n.d.). Probability for Computer Scientists.

Learn Data Mining

• Zaki, M. J., & Meira, W. (2014). Data Mining and Analysis: Fundamental Concepts and Algorithms. Cambridge University Press.

Learn Machine Learning

• Hagan, M. T., Demuth, H. B., Beale, M. H., & De Jesús, O. (2014). Neural Network Design (2nd ed.).

Learn Deep Learning

• Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.

Generative AI 🤖

Understanding generative AI tools like ChatGPT, Claude, and Perplexity can help you explore cutting-edge developments in artificial intelligence. These platforms can assist you in coding by generating code snippets, debugging errors, and explaining complex programming concepts, making your learning process more efficient and interactive.

ChatGPT

Claude

Perplexity

R Libraries 📊

These R libraries provide essential tools for data visualization, manipulation, and statistical modeling. Whether you’re working with data frames, building interactive dashboards, or applying machine learning, these packages will streamline your workflow.

install.packages("ggplot2")
install.packages("dplyr")
install.packages("tidyverse")
install.packages("shiny")
install.packages("caret")
install.packages("readr")

Python Libraries 🐍

Python is the backbone of modern data science, and these libraries provide crucial functionalities for data analysis, machine learning, and deep learning. Mastering these will enable you to efficiently process data, create models, and visualize results.

pip install numpy
pip install pandas
pip install matplotlib
pip install seaborn
pip install scikit-learn
pip install tensorflow
pip install torch