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Data Scientist Roadmap

1
Statistics
Descriptive Statistics
P Value
Probability Table
Hypothesis Test
Bayesian Inference
Significance Level
Probability Distributions
Mathematics
Mathematics for Data Scientists
2
Linear Algebra
Calculus
Graph Theory
Matrix Factorization
Combinatorics
3
Programming Skills
Terminal Usage
Use of Jupyter Notebook
Algorithm Efficiency and Code Optimization
Version Control
4
Programming Languages
Python
R
Database Query
SQL
5
Business Analytics
Table
D3.js
A/B Testing
Metric Design
Soft Skills
6
Engineering
Distributed Database System
Parallel Databases
MapReduce
Hadoop Ecosystem
Cloud Infrastructure Platforms
7
Data Cleaning
Outlier Values Management
Missing Data Management
8
Producing Model
Classification
Clustering
Estimation Modeling
9
Feature Engineering
What is Feature Engineering?
10
Model Evaluation
In Sample vs Out of Sample
Overlearning and Underlearning
Measurement Metrics
Model Development
Regularization
Dimensional Reduction
Hyperparameter Optimization
Community Methods
11
Algorithms
Decision Tree
K Means
SVM
Logistic Regression
Spectral Clustering
KNN
12
Advanced Mathematical Concepts
13
Deep Learning
RNN (Recurrent Neural Networks)
ANN (Artificial Neural Networks)
CNN (Convolutional Neural Networks)
14
NLP (Natural Language Processing)
TF- IDF
POS Tagger
Hidden Markov Model
Emotion Analysis
15
Visual Recognition and Computer Vision
Computer Vision
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