README.md

DataCamp

• Courses

  • Reinforcement Learning with Gymnasium in Python
  • Deep Reinforcement Learning in Python
  • Introduction to Optimization in Python
  • Analyzing Marketing Campaigns with pandas
  • Predicting CTR with Machine Learning in Python
  • Market Basket Analysis in Python
  • Building Recommendation Engines in Python
  • Survival Analysis in Python
  • Introduction to Network Analysis in Python
  • Intermediate Network Analysis in Python
  • Structural Equation Modeling with lavaan in R
  • Discrete Event Simulation in Python
  • Introduction to Data Warehousing
  • Data Management Concepts
  • Understanding Modern Data Architecture
  • Introduction to dbt
  • Introduction to Docker
  • Intermediate Docker
  • CI/CD for Machine Learning
  • Introduction to Azure
  • Introduction to AWS
  • Working with Llama 3
  • Intermediate ChatGPT
  • Decoding Decision Modeling
  • Explainable AI in Python
  • Retrieval Augmented Generation (RAG) with LangChain
  • Designing Agentic Systems with LangChain
  • Introduction to FastAPI

• Skill Tracks

  • Marketing Analytics with Python

    • Marketing Analytics: Predicting Customer Churn in Python
    • Customer Analytics and A/B Testing in Python
    • Customer Segmentation in Python
    • Machine Learning for Marketing in Python

  • Marketing Analytics with R

    • Choice Modeling for Marketing in R
    • Building Response Models in R
    • Introduction to Text Analysis in R

  • Time Series with Python

    • Visualizing Time Series Data in Python

  • Data Visualization with Python

    • Introduction to Data Visualization with Seaborn
    • Interactive Data Visualization with Bokeh

  • Machine Learning Fundamentals with Python

    • Unsupervised Learning in Python

  • Deep Learning in Python

    • Introduction to TensorFlow in Python
    • Introduction to Deep Learning with PyTorch

  • Unsupervised Machine Learning with R

    • Factor Analysis in R
    • Advanced Dimensionality Reduction in R

  • Deep Learning for NLP in Python

    • Recurrent Neural Networks for Language Modeling in Python

  • Natural Language Processing in Python

    • Introduction to Natural Language Processing in Python

  • Data Manipulation with Python

    • Merging DataFrames with pandas
    • Reshaping Data with pandas

  • Probability and Distributions with R

    • Mixture Models in R
    • Probability Puzzles in R

  • Big Data with PySpark

    • Building Recommendation Engines with PySpark

  • MLOps Fundamentals

    • MLOps Concepts
    • Developing Machine Learning Models for Production
    • MLOps Deployment and Life Cycling
    • Fully Automated MLOps

  • Julia Fundamentals

    • Introduction to Julia
    • Intermediate Julia
    • Data Manipulation in Julia
    • Introduction to Data Visualization with Julia

  • AI Business Fundamentals

    • Introduction to ChatGPT

• Career Tracks

  • Data Engineer with Python
    • Introduction to Airflow in Python
  • Data Scientist Professional with Python
    • Introduction to Data Visualization with Seaborn
    • Unsupervised Learning in Python
  • Machine Learning Scientist with Python
    • Unsupervised Learning in Python
    • Cluster Analysis in Python
    • Introduction to TensorFlow in Python
  • Statistician with R
    • Experimental Design in R
    • A/B Testing in R

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Roadmap