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- User Authentication
- Hasan Palta's Credentials
- Hasan Palta's Wallet
- Track 1: Deep Learning Foundations
- Principles of Data Literacy
- Exploratory Data Analysis in Python
- Learn Tableau for Data Visualization
- Welcome to the Data Scientist: Analytics Specialist Career Path
- Learn SQL
- Python Fundamentals for Data Science (Part I)
- Python Pandas for Data Science
- Learn Microsoft Excel for Data Analysis
- Data Wrangling, Cleaning, and Tidying
- Statistics Fundamentals for Data Science
- Data Visualization Fundamentals with Python
- Portfolio Project: Data Visualization
- Communicating Data Science Findings
- Data Science Foundations Portfolio Project
- Advanced Exploratory Data Analysis
- Visualization for Data Science Applications
- Advanced SQL for Data Science
- Data Scientist: Analytics Specialist Final Portfolio Project
- Data Scientist: Analytics
- Causal Inference Fundamentals
- Data Scientist: Inference Specialist
- Advanced SQL for Data Science
- Statistics Fundamentals Part II
- Regression for Inference Data Science
- R for Programmers
- Track 1: Python for Data Science
- Data Science Foundations
- Principles of Data Literacy
- Exploratory Data Analysis in Python
- Welcome to the Data Scientist: Inference Specialist Career Path
- Python Fundamentals for Data Science (Part I)
- Python Fundamentals for Data Science (Part II)
- Python Pandas for Data Science
- Math for Inference Data Science
- Learn SQL
- Statistics Fundamentals for Data Science
- Data Visualization Fundamentals with Python
- Data Wrangling, Cleaning, and Tidying
- Communicating Data Science Findings
- Portfolio Project: Data Visualization
- Advanced Exploratory Data Analysis
- Data Scientist: Inference Final Portfolio Project
- Track 2: Exploratory Data Analysis with Python
- Track 3: Data Visualization with Python
- Track 5: Introductory Statistics
- Track 4: Data Cleaning with Python
- Track 1: Learn Python 3
- Final Exam: Working with Microsoft Azure SQL
- Track 2: Supervised Learning I : Linear and Logistic Regression
- Beginner Machine Learning
- Build Chatbots
- Data Scientist: Natural Language Processing Specialist
- Track 4: Fundamentals of Language Models
- NLP
- NLP Portfolio Project
- Track 1: Introduction to Machine Learning
- Track 3: Supervised Learning II: Naive Bayes, SVM, KNN and Decision Trees
- Learn Tableau for Data Visualization
- Track 1: Learn Tableau for Data Visualization
- Natural Language Processing: Getting Started with NLP
- Getting Started with Natural Language Processing
- Principles of Data Literacy
- Text Preprocessing
- Exploratory Data Analysis in Python
- Welcome to the Data Scientist: Natural Language Processing Specialist Career Path
- Deep Learning and Neural Networks
- Python Pandas for Data Science
- Python Fundamentals for Data Science (Part II)
- Python Fundamentals for Data Science (Part I)
- Data Science Foundations Portfolio Project
- Machine Learning Fundamentals
- Supervised Learning I : Regressors, Classifiers and Trees
- Unsupervised Learning Algorithms I
- Learn SQL
- Communicating Data Science Findings
- Data Wrangling, Cleaning, and Tidying
- Machine Learning Portfolio Project
- Data Visualization Fundamentals with Python
- Portfolio Project: Data Visualization
- Language Quantification
- Math for Machine Learning
- Supervised Learning II: SVM's, Random Forests, Naive Bayes
- Python Fundamentals Part III
- Language Parsing
- Statistics Fundamentals for Data Science
- Text Generation
- Text Generation
- Track 3: Bag-of-Words and TF-IDF
- Track 2: RegEx and Text Preprocessing
- Track 3: Make Charts with Seaborn
- Data Visualization with Python
- Track 1: Getting Started with Natural Language Processing
- Track 2: Make a Visual Argument with Matplotlib
- Track 1: Make Charts with Matplotlib
- Deep Learning and Neural Networks
- Supervised Learning II: SVM's, Recommender Systems, Naive Bayes
- Data Scientist: Machine Learning
- Machine Learning Portfolio Project
- Track 4: Recommender Systems
- Ensemble Methods in Machine Learning
- Track 5: Unsupervised Learning; K Means Clustering and PCA
- Unsupervised Learning Algorithms
- Feature Engineering for Data Scientists
- Supervised Learning I : Regressors, Classifiers and Trees
- Statistics Fundamentals Part II
- Python Fundamentals Part III
- Data Wrangling, Cleaning, and Tidying
- Learn C
- C
- Machine Learning Fundamentals
- Data Science Foundations Portfolio Project
- Statistics Fundamentals for Data Science
- Math for Machine Learning
- Portfolio Project: Data Visualization
- Exploratory Data Analysis in Python
- Data Visualization Fundamentals with Python
- Next Step: The Machine Learning Specialty
- Python Fundamentals for Data Science (Part II)
- Python Pandas for Data Science
- Python Fundamentals for Data Science (Part I)
- Learn SQL
- Principles of Data Literacy
- MATLAB Fundamentals
- Getting Started with MATLAB
- Welcome to the Data Scientist: Machine Learning Specialist Career Path
- Track 4: SQL for Marketers and Product Managers
- Analyze Data with SQL
- Track 1: SQL Basics
- Track 3: Intermediate SQL Functions
- Track 2: Aggregates, Multiple Tables, and Subqueries with SQL
- Hasan Palta's Transcript
- Hasan Palta's Wallet
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