Data Scientist
Build a career as a data scientist, combining statistics, machine learning, and business acumen to solve complex problems.
Key Skills to Learn
Learning Path
Python Fundamentals
Master Python basics including data structures, functions, and object-oriented programming.
Duration: 4-6 weeks
Data Manipulation & Analysis
Learn Pandas and NumPy to work with data efficiently.
Duration: 4-6 weeks
Statistics & Probability
Build a strong foundation in statistical concepts needed for ML.
Duration: 6-8 weeks
Data Visualization
Learn to create compelling visualizations with Matplotlib, Seaborn, and Plotly.
Duration: 2-3 weeks
Machine Learning Fundamentals
Understand supervised and unsupervised learning algorithms.
Duration: 8-10 weeks
Advanced Machine Learning
Deep dive into advanced techniques and deep learning.
Duration: 8-10 weeks
SQL & Databases
Learn to work with databases and extract data efficiently.
Duration: 4-6 weeks
Real-World Projects
Build 3-5 end-to-end projects to demonstrate your skills.
Duration: 8-12 weeks
Tools & Technologies
Programming
- • Python
- • Jupyter Notebook
- • VS Code
Data Processing
- • Pandas
- • NumPy
- • SciPy
Machine Learning
- • Scikit-learn
- • TensorFlow
- • PyTorch
Visualization
- • Matplotlib
- • Seaborn
- • Plotly
- • Tableau
Databases
- • SQL
- • PostgreSQL
- • MongoDB
Collaboration
- • Git
- • GitHub
- • Jupyter
- • Google Colab
Hands-On Projects
Iris Flower Classification
Classic beginner project: predict iris flower species using multiple classification algorithms.
Housing Price Prediction
Predict house prices using regression techniques on the Boston Housing dataset.
Customer Churn Analysis
Analyze and predict customer churn for a telecom company using advanced classification methods.
Movie Recommendation System
Build a recommendation system using collaborative filtering and matrix factorization.
Time Series Forecasting
Forecast stock prices or weather using LSTM networks and time series models.
NLP Sentiment Analysis
Build a sentiment analysis model on social media data or product reviews.
Learning Resources
Online Courses
- • Andrew Ng's Machine Learning Course (Coursera)
- • Fast.ai - Practical Deep Learning
- • DataCamp Data Science Track
- • Kaggle Learn Micro-Courses
Books
- • Python for Data Analysis by Wes McKinney
- • Hands-On Machine Learning by Aurélien Géron
- • Statistical Rethinking by Richard McElreath
- • Deep Learning by Goodfellow, Bengio, and Courville
Practice
- • Kaggle Competitions
- • LeetCode
- • HackerRank
- • DataCamp Challenges