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Free Lessons (7)
Are You Ready to Become a Data Scientist?
Data Science and YOU!
Data Science Process Pipeline
Advancements in Data Science
Python Basics
Introduction to Python
Variables
Decision Making
Loops
Functions
List and Tuple
Dictionary
Classes and Methods
Python Libraries
NumPy
SciPy
Pandas
Data Visualization
Scikit-learn
TensorFlow
More Data Science Tools
KNIME
R
Orange
Tableau
Jupyter
Weka
Cloud ML Engines
Data Structures and Algorithms - I
Why Data Structures and Algorithms are Important
Array
Linked List
Stack
Queue
Trees
Hash Tables
Data Structures and Algorithms - II
Greedy Algorithms
Divide and Conquer
Backtracking
Dynamic Programming
Statistics and Probability
Data Exploration
Correlation
Basics of Probability
Conditional Probability
Random Variable
Normal and Binomial Distribution
Feature Engineering
The Need for Feature Engineering
Numerical Features
Categorical Features
Date and Time Features
Missing Data
Putting Everything Together!
Basics of Machine Learning
Types of ML Problems
Measuring ML Model Performance
Improving ML Model Performance
Regression
Simple Regression
Multiple Regression
Regularized Regression
Nonparametric Regression
Regression Model Assessment
Classification
Linear Classifiers
Logistic Regression
Naïve Bayes
Decision Trees
Random Forest
Adaboost
Classification Model Assessment
Unsupervised Learning
Nearest Neighbors
KMeans Clustering
Probabilistic Clustering
Hierarchical Clustering
Advanced Topics in Machine Learning
Neural Network and Deep Learning
Issues in Deep Learning
Recommendation Engines
Natural Language Processing
Conclusion
This is The Beginning!
Mega Quiz
Practice Mock Interview
Data Science Interview Handbook
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Mega Quiz
Mega Quiz
A mega quiz to test your knowledge about this course.
We'll cover the following...
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