Curriculum
Course:
DATA Science
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Curriculum
DATA Science
Introduction to Data Science
0/4
JavaScript Fundamentals
Text lesson
Developer Skills & Editor Setup
Text lesson
Applications of Data Science
Text lesson
Roles and Responsibilities of a Data Scientist
Text lesson
Mathematics and Statistics for Data Science
0/6
Basic Structure of a Blockchain Block
Text lesson
Blockchain Data Structure: Merkle Trees
Preview
Cryptography in Blockchain
Text lesson
Inferential Statistics (hypothesis testing, p-values, confidence intervals)
Text lesson
Sampling Methods and Estimations
Text lesson
Regression Analysis (simple and multiple)
Text lesson
Programming for Data Science
0/6
Introduction to Python or R
Text lesson
Python Libraries: NumPy, Pandas, Matplotlib, Seaborn
Text lesson
R Libraries: ggplot2, dplyr, tidyr
Text lesson
Data Structures (lists, arrays, dataframes)
Text lesson
Functions, Loops, and Conditional Statements
Text lesson
File Handling (reading, writing data from CSV, JSON, SQL)
Text lesson
Data Preprocessing
0/4
Data Cleaning (handling missing data, outliers
Text lesson
Data Transformation (scaling, encoding, normalization)
Text lesson
Feature Engineering (creating new features, feature selection
Text lesson
Text Data Processing (tokenization, stopwords, TF-IDF)
Text lesson
Exploratory Data Analysis (EDA)
0/5
Data Visualization (histograms, boxplots, scatterplots, etc.)
Text lesson
Correlation and Covariance
Text lesson
Identifying trends and patterns
Text lesson
Summary Statistics
Text lesson
Using Matplotlib, Seaborn, and Plotly for visualizations
Text lesson
Machine Learning
0/11
Supervised Learning
Text lesson
Linear Regression
Text lesson
Logistic Regression
Text lesson
Decision Trees and Random Forests
Text lesson
Support Vector Machines (SVM)
Text lesson
k-Nearest Neighbors (k-NN
Text lesson
Neural Networks
Text lesson
Unsupervised Learning:
Text lesson
Clustering K-means, Hierarchical
Text lesson
Dimensionality Reduction (PCA, t-SNE)
Text lesson
Model Evaluation
Text lesson
Deep Learning
0/5
Introduction to Neural Networks
Text lesson
Backpropagation and Gradient Descent
Text lesson
Convolutional Neural Networks (CNNs
Text lesson
Recurrent Neural Networks (RNNs) and LSTMs
Text lesson
TensorFlow and Keras
Text lesson
Natural Language Processing (NLP)
0/5
Text Preprocessing
Text lesson
Bag-of-Words, TF-IDF, Word2Vec
Text lesson
Sentiment Analysis
Text lesson
Named Entity Recognition (NER)
Text lesson
Text Classification and Clustering
Text lesson
Big Data and Data Engineering
0/5
Introduction to Big Data Tools
Text lesson
Distributed Data Processing
Text lesson
Working with NoSQL Databases
Text lesson
Data Pipelines and ETL
Text lesson
Cloud Platform
Text lesson
Model Deployment and Production
0/5
Model Deployment using Flask/Django
Text lesson
Introduction to REST APIs
Text lesson
Cloud Deployment
Text lesson
Continuous Integration and Continuous Deployment
Text lesson
Model Monitoring and Maintenance
Text lesson
Capstone Project
0/3
Working on a real-world dataset
Text lesson
Applying Data Science techniques
Text lesson
Presenting results and insights using visualizations
Text lesson
Text lesson
Blockchain Data Structure: Merkle Trees
Blockchain Data Structure: Merkle Trees
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