Categories Reflections Week 11 - Project Mothership News Crawler - Web Scraping using Requests and BeautifulSoup Week 10 - Project Titanic - EDA using Pandas and Seaborn Week 9 - Pandas (Part I) - Introduction, Data input and validation, create columns & dataframes Week 8 - NumPy (Part I) - Introduction to NumPy Week 8 - Additional Practices for handling Text Files Week 7 - How to Handle Files in Python Week 7 - More ways to use loops and strings Week 6 - Exploring more Python Lists attributes Week 5 - Taking a deeper dive into Python Strings Week 5 - Additional Practice Problems Week 4 - Using assignment operators, custom functions within functions, return values Week 4 - Programming patterns across languages & using pass, flag, break Week 3 - Knowing more Python built-in functions Week 3 - Understanding Dictionaries & List comprehension Week 2 - Learning more basic Python functions, libraries, attributes Week 1 - User-defined Functions Week 1 - First Day of Learning Python and Markdown Week 1 - Initial Challenges & Next Steps in My Programming Journey Learning Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 15 - Machine Learning - (Supervised Learning) Classification from Principles of M.L. Python by Microsoft Learning Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Multivariate Linear Regression from M.L. course by Stanford Uni (Week 2 Part I) Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Classification model using K-Nearest Neighbor (KNN) for iris from Principles of M.L. Python by Microsoft Learning Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from M.L. course by Stanford Uni (Week 1 Part IV) Week 13 - Machine Learning - Unsupervised Learning from M.L. course by Stanford Uni (Week 1 Part III) Week 13 - Machine Learning - Supervised Learning from M.L. course by Stanford Uni (Week 1 Part II) Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I) Week 11 - Descriptive Statistics - Fundamentals Week 11 - Web Scraping with Requests and BeautifulSoup Week 10 - Matplotlib and Seaborn & Data and Visualisations Week 10 - Pandas (Part V) - Exploratory Data Analysis Week 10 - Pandas (Part IV) - Transforming Databases Week 9 - Pandas (Part III) - Settings and options, Advanced Calculations Week 9 - Pandas (Part II) - Basic Analysis, Indexes Week 9 - Pandas (Part I) - Introduction, Data input and validation, create columns & dataframes Week 8 - NumPy (Part II) - 2D NumPy Arrays, Basic Statistics Week 8 - NumPy (Part I) - Introduction to NumPy Week 8 - More VScode commands for Python libraries, Jupyter Notebook, Git, Markdown Week 7 - How to Handle Files in Python Week 7 - More ways to use loops and strings Week 7 - Getting familiar with Git and using VSCode for Git Week 6 - Anaconda & VScode installation, uses and commands Week 6 - Exploring more Python Lists attributes Week 5 - Taking a deeper dive into Python Strings Week 4 - Using assignment operators, custom functions within functions, return values Week 4 - Programming patterns across languages & using pass, flag, break Week 3 - Knowing more Python built-in functions Week 3 - Understanding Dictionaries & List comprehension Week 2 - Escape sequences, Additional Basic Practice Problems Week 2 - Learning more basic Python functions, libraries, attributes Week 1 - User-defined Functions Week 1 - First Day of Learning Python and Markdown Python Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 15 - Machine Learning - (Supervised Learning) Classification from Principles of M.L. Python by Microsoft Learning Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Multivariate Linear Regression from M.L. course by Stanford Uni (Week 2 Part I) Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Classification model using K-Nearest Neighbor (KNN) for iris from Principles of M.L. Python by Microsoft Learning Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from M.L. course by Stanford Uni (Week 1 Part IV) Week 13 - Machine Learning - Unsupervised Learning from M.L. course by Stanford Uni (Week 1 Part III) Week 13 - Machine Learning - Supervised Learning from M.L. course by Stanford Uni (Week 1 Part II) Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I) Week 11 - Descriptive Statistics - Fundamentals Week 11 - Project Mothership News Crawler - Web Scraping using Requests and BeautifulSoup Week 11 - Web Scraping with Requests and BeautifulSoup Week 10 - Project Titanic - EDA using Pandas and Seaborn Week 10 - Matplotlib and Seaborn & Data and Visualisations Week 10 - Pandas (Part V) - Exploratory Data Analysis Week 10 - Pandas (Part IV) - Transforming Databases Week 9 - Pandas (Part III) - Settings and options, Advanced Calculations Week 9 - Pandas (Part II) - Basic Analysis, Indexes Week 9 - Pandas (Part I) - Introduction, Data input and validation, create columns & dataframes Week 8 - NumPy (Part II) - 2D NumPy Arrays, Basic Statistics Week 8 - NumPy (Part I) - Introduction to NumPy Week 8 - More VScode commands for Python libraries, Jupyter Notebook, Git, Markdown Week 8 - Additional Practices for handling Text Files Week 7 - How to Handle Files in Python Week 7 - More ways to use loops and strings Week 7 - Getting familiar with Git and using VSCode for Git Week 6 - Anaconda & VScode installation, uses and commands Week 6 - Exploring more Python Lists attributes Week 5 - Taking a deeper dive into Python Strings Week 5 - Additional Practice Problems Week 4 - Using assignment operators, custom functions within functions, return values Week 4 - Programming patterns across languages & using pass, flag, break Week 3 - Knowing more Python built-in functions Week 3 - Understanding Dictionaries & List comprehension Week 2 - Escape sequences, Additional Basic Practice Problems Week 2 - Learning more basic Python functions, libraries, attributes Week 1 - User-defined Functions Week 1 - First Day of Learning Python and Markdown Markdown Week 8 - More VScode commands for Python libraries, Jupyter Notebook, Git, Markdown Week 1 - First Day of Learning Python and Markdown Practices Week 8 - NumPy (Part II) - 2D NumPy Arrays, Basic Statistics Week 8 - NumPy (Part I) - Introduction to NumPy Week 8 - Additional Practices for handling Text Files Week 7 - How to Handle Files in Python Week 7 - More ways to use loops and strings Week 6 - Exploring more Python Lists attributes Week 5 - Taking a deeper dive into Python Strings Week 5 - Additional Practice Problems Week 4 - Using assignment operators, custom functions within functions, return values Week 4 - Programming patterns across languages & using pass, flag, break Week 3 - Knowing more Python built-in functions Week 3 - Understanding Dictionaries & List comprehension Week 2 - Escape sequences, Additional Basic Practice Problems Week 2 - Learning more basic Python functions, libraries, attributes Week 1 - User-defined Functions Week 1 - First Day of Learning Python and Markdown Cheatsheets Week 11 - Web Scraping with Requests and BeautifulSoup Week 10 - Matplotlib and Seaborn & Data and Visualisations Week 9 - Pandas (Part I) - Introduction, Data input and validation, create columns & dataframes Week 8 - NumPy (Part I) - Introduction to NumPy Week 7 - Getting familiar with Git and using VSCode for Git Week 5 - Taking a deeper dive into Python Strings Week 1 - First Day of Learning Python and Markdown References Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I) Week 11 - Web Scraping with Requests and BeautifulSoup Week 10 - Project Titanic - EDA using Pandas and Seaborn Week 10 - Matplotlib and Seaborn & Data and Visualisations Week 10 - Pandas (Part V) - Exploratory Data Analysis Week 10 - Pandas (Part IV) - Transforming Databases Week 9 - Pandas (Part II) - Basic Analysis, Indexes Week 9 - Pandas (Part I) - Introduction, Data input and validation, create columns & dataframes Week 8 - More VScode commands for Python libraries, Jupyter Notebook, Git, Markdown Week 8 - Additional Practices for handling Text Files Week 7 - Getting familiar with Git and using VSCode for Git Week 6 - Anaconda & VScode installation, uses and commands Week 5 - Taking a deeper dive into Python Strings Week 1 - First Day of Learning Python and Markdown Anaconda Week 6 - Anaconda & VScode installation, uses and commands VSCode Week 8 - More VScode commands for Python libraries, Jupyter Notebook, Git, Markdown Week 7 - How to Handle Files in Python Week 7 - Getting familiar with Git and using VSCode for Git Week 6 - Anaconda & VScode installation, uses and commands Git Week 8 - More VScode commands for Python libraries, Jupyter Notebook, Git, Markdown Week 7 - Getting familiar with Git and using VSCode for Git NumPy Week 8 - NumPy (Part II) - 2D NumPy Arrays, Basic Statistics Week 8 - NumPy (Part I) - Introduction to NumPy Pandas Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 10 - Project Titanic - EDA using Pandas and Seaborn Week 10 - Pandas (Part V) - Exploratory Data Analysis Week 10 - Pandas (Part IV) - Transforming Databases Week 9 - Pandas (Part III) - Settings and options, Advanced Calculations Week 9 - Pandas (Part II) - Basic Analysis, Indexes Week 9 - Pandas (Part I) - Introduction, Data input and validation, create columns & dataframes Kaggle Week 9 - Pandas (Part I) - Introduction, Data input and validation, create columns & dataframes Matplotlib Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 10 - Matplotlib and Seaborn & Data and Visualisations Seaborn Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 10 - Project Titanic - EDA using Pandas and Seaborn Week 10 - Matplotlib and Seaborn & Data and Visualisations Project Week 11 - Project Mothership News Crawler - Web Scraping using Requests and BeautifulSoup Week 10 - Project Titanic - EDA using Pandas and Seaborn Web Scraping Week 11 - Project Mothership News Crawler - Web Scraping using Requests and BeautifulSoup Week 11 - Web Scraping with Requests and BeautifulSoup Requests Week 11 - Project Mothership News Crawler - Web Scraping using Requests and BeautifulSoup Week 11 - Web Scraping with Requests and BeautifulSoup BeautifulSoup Week 11 - Project Mothership News Crawler - Web Scraping using Requests and BeautifulSoup Week 11 - Web Scraping with Requests and BeautifulSoup Statistics Week 11 - Descriptive Statistics - Fundamentals Machine Learning Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 15 - Machine Learning - (Supervised Learning) Classification from Principles of M.L. Python by Microsoft Learning Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Multivariate Linear Regression from M.L. course by Stanford Uni (Week 2 Part I) Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning Week 14 - Machine Learning - (Supervised Learning) Classification model using K-Nearest Neighbor (KNN) for iris from Principles of M.L. Python by Microsoft Learning Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from M.L. course by Stanford Uni (Week 1 Part IV) Week 13 - Machine Learning - Unsupervised Learning from M.L. course by Stanford Uni (Week 1 Part III) Week 13 - Machine Learning - Supervised Learning from M.L. course by Stanford Uni (Week 1 Part II) Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I)
Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Classification from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Multivariate Linear Regression from M.L. course by Stanford Uni (Week 2 Part I)
Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Classification model using K-Nearest Neighbor (KNN) for iris from Principles of M.L. Python by Microsoft Learning
Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval
Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from M.L. course by Stanford Uni (Week 1 Part IV)
Week 13 - Machine Learning - Unsupervised Learning from M.L. course by Stanford Uni (Week 1 Part III)
Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning
Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I)
Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Classification from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Multivariate Linear Regression from M.L. course by Stanford Uni (Week 2 Part I)
Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Classification model using K-Nearest Neighbor (KNN) for iris from Principles of M.L. Python by Microsoft Learning
Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval
Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from M.L. course by Stanford Uni (Week 1 Part IV)
Week 13 - Machine Learning - Unsupervised Learning from M.L. course by Stanford Uni (Week 1 Part III)
Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning
Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I)
Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning
Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval
Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning
Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I)
Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Applying Linear Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Classification from Principles of M.L. Python by Microsoft Learning
Week 15 - Machine Learning - (Supervised Learning) Introduction to Regression from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Multivariate Linear Regression from M.L. course by Stanford Uni (Week 2 Part I)
Week 14 - Machine Learning - Data Preparation for automobile prices & german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Classification for german bank credit from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Visualizing Data for Regression for automobile prices from Principles of M.L. Python by Microsoft Learning
Week 14 - Machine Learning - (Supervised Learning) Classification model using K-Nearest Neighbor (KNN) for iris from Principles of M.L. Python by Microsoft Learning
Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from Youtube by Siraj Raval
Week 13 - Machine Learning - (Supervised Learning) Linear Regression, Cost Function, Gradient Descent from M.L. course by Stanford Uni (Week 1 Part IV)
Week 13 - Machine Learning - Unsupervised Learning from M.L. course by Stanford Uni (Week 1 Part III)
Week 12 - Machine Learning - Semi-supervised Learning, Reinforcement Learning from Fundamentals of A.I. & M.L. by LinkedIn Learning
Week 12 - Machine Learning - Intro to Machine Learning from M.L. course by Stanford Uni (Week 1 Part I)
