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Data Science
Extract Powerful Insights from Data
Salary Expectations (₹ INR, per annum)
Fresher
₹6 – ₹10 LPA
Mid-Level
₹12 – ₹22 LPA
Senior
₹25 – ₹50+ LPA
Detailed Learning Path
1
Mathematics & Statistics Foundation
4–6 WeeksThis is the theoretical backbone of data science. Understanding these concepts is essential for building effective models.
Key Topics to Cover
Linear Algebra — Vectors, Matrices, and operations — crucial for understanding how ML algorithms process data.
Calculus — Derivatives and Gradients — the core of how models learn and optimize.
Statistics & Probability — Descriptive Stats (mean, median), Inferential Stats, Probability Distributions, and Hypothesis Testing.
Recommended Resources
StatQuest with Josh Starmer YouTube
Complex stats and ML topics made incredibly simple.
Khan Academy: Statistics Free Course
Complete curriculum from basics to advanced topics.
2
Python for Data Science
6–8 WeeksLearn the most popular language for data science and its powerful libraries for data manipulation and analysis.
Key Topics to Cover
Python Fundamentals — Variables, data types, loops, functions, and OOP basics.
NumPy — N-dimensional arrays for fast numerical computation.
Pandas — DataFrames for data cleaning, manipulation, filtering, and aggregation (groupby).
Matplotlib & Seaborn — Static, animated, and interactive visualizations to explore data and present results.
Recommended Resources
Nerchuko YouTube Channel
Excellent explanations of complex topics in Telugu/English.
Krish Naik YouTube Channel
End-to-end data science projects and tutorials.
3
Machine Learning Fundamentals
8–12 WeeksLearn to build predictive models to forecast future events or classify information.
Key Topics to Cover
Supervised Learning — Regression (Linear Regression) and Classification (Logistic Regression, Decision Trees).
Unsupervised Learning — Clustering algorithms like K-Means to find patterns in unlabelled data.
The ML Workflow — Data Preprocessing, Feature Engineering, Model Training, and Evaluation (Accuracy, F1-Score).
Scikit-Learn Mastery — Python's primary ML library for implementing most of these models.
Recommended Resources
Machine Learning by Andrew Ng Coursera
The most famous and respected ML course in the world.
Hands-On Machine Learning Book
A practical guide using Scikit-Learn, Keras & TensorFlow.