Skip to Content on-demand course Data Science and Machine Learning (Theory and Projects) A to Z November 2021
Beginner
93h 30m
English
Closed Captioning available in English Course outline Chapter 1 : Introduction to the Course 21m
Chapter 2 : Basics for Data Science: Python for Data Science and Data Analysis 13h 57m
Introduction - Part 110m 54s
Introduction - Part 27m 42s
Basics of Programming: Understanding the Algorithm12m 29s
Basics of Programming: FlowCharts and Pseudocodes9m 49s
Basics of Programming: Example of Algorithms - Making Tea Problem12m 33s
Basics of Programming: Example of Algorithms-Searching Minimum15m 48s
Basics of Programming: Example of Algorithms-Sorting Problem7m 20s
Basics of Programming: Sorting Problem in Python10m 34s
Why Python and Jupyter Notebook: Why Python9m 0s
Why Python and Jupyter Notebook: Why Jupyter Notebooks12m 52s
Installation of Anaconda and IPython Shell: Installing Python and Jupyter Anaconda4m 24s
Installation of Anaconda and IPython Shell: Your First Python Code - Hello World9m 12s
Installation of Anaconda and IPython Shell: Coding in IPython Shell7m 13s
Variable and Operator: Variables15m 55s
Variable and Operator: Operators13m 39s
Variable and Operator: Variable Name Quiz5m 2s
Variable and Operator: Bool Data Type in Python6m 6s
Variable and Operator: Comparison in Python7m 19s
Variable and Operator: Combining Comparisons in Python11m 2s
Variable and Operator: Combining Comparisons Quiz3m 59s
Python Useful function: Python Function- Round5m 37s
Python Useful function: Python Function- Divmod4m 28s
Python Useful function: Python Function- Is instance and PowFunctions6m 7s
Python Useful function: Python Function- Input8m 48s
Control Flow in Python: If Python Condition12m 7s
Control Flow in Python: if Elif Else Python Conditions8m 46s
Control Flow in Python: More on if Elif Else Python Conditions11m 1s
Control Flow in Python: Indentations13m 23s
Control Flow in Python: Comments and Problem-Solving Practice with If16m 51s
Control Flow in Python: While Loop8m 24s
Control Flow in Python: While Loop Break Continue12m 12s
Control Flow in Python: For Loop8m 15s
Control Flow in Python: Else in For Loop9m 48s
Control Flow in Python: Loops Practice-Sorting Problem12m 23s
Function and Module in Python: Functions in Python8m 38s
Function and Module in Python: DocString8m 23s
Function and Module in Python: Input Arguments8m 53s
Function and Module in Python: Multiple Input Arguments9m 44s
Function and Module in Python: Ordering Multiple Input Arguments7m 9s
Function and Module in Python: Output Arguments and Return Statement7m 20s
Function and Module in Python: Function Practice-Output Arguments and Return Statement13m 45s
Function and Module in Python: Variable Number of Input Arguments7m 48s
Function and Module in Python: Variable Number of Input Arguments as Dictionary8m 6s
Function and Module in Python: Default Values in Python11m 30s
Function and Module in Python: Modules in Python5m 28s
Function and Module in Python: Making Modules in Python15m 43s
Function and Module in Python: Function Practice-Sorting List in Python27m 30s
String in Python: Strings9m 31s
String in Python: Multi-Line Strings5m 50s
String in Python: Indexing Strings14m 9s
String in Python: String Methods14m 56s
String in Python: String Escape Sequences10m 9s
Data Structure (List, Tuple, Set, Dictionary): Introduction to Data Structure6m 47s
Data Structure (List, Tuple, Set, Dictionary): Defining and Indexing10m 27s
Data Structure (List, Tuple, Set, Dictionary): Insertion and Deletion7m 30s
Data Structure (List, Tuple, Set, Dictionary): Python Practice-Insertion and Deletion6m 36s
Data Structure (List, Tuple, Set, Dictionary): Deep Copy or Reference Slicing8m 25s
Data Structure (List, Tuple, Set, Dictionary): Exploring Methods Using TAB Completion7m 23s
Data Structure (List, Tuple, Set, Dictionary): Data Structure Abstract Ways6m 32s
Data Structure (List, Tuple, Set, Dictionary): Data Structure Practice19m 39s
NumPy for Numerical Data Processing: Introduction to NumPy6m 49s
NumPy for Numerical Data Processing: NumPy Dimensions13m 52s
NumPy for Numerical Data Processing: NumPy Shape, Size, and Bytes4m 41s
NumPy for Numerical Data Processing: Arrange, Random, and Reshape-Part 19m 0s
NumPy for Numerical Data Processing: Arrange, Random, and Reshape-Part 210m 23s
NumPy for Numerical Data Processing: Slicing-Part 111m 26s
NumPy for Numerical Data Processing: Slicing-Part 27m 56s
NumPy for Numerical Data Processing: NumPy Masking8m 37s
NumPy for Numerical Data Processing: NumPy BroadCasting and Concatenation10m 15s
NumPy for Numerical Data Processing: NumPy ufuncs Speed Test6m 28s
Pandas for Data Manipulation: Introduction to Pandas6m 58s
Pandas for Data Manipulation: Pandas Series6m 23s
Pandas for Data Manipulation: Pandas Data Frame8m 51s
Pandas for Data Manipulation: Pandas Missing Values6m 43s
Pandas for Data Manipulation: Pandas .loc and .iloc6m 46s
Pandas for Data Manipulation: Pandas Practice-Using COVID19 Data - Part 114m 11s
Pandas for Data Manipulation: Pandas Practice-Using COVID19 Data - Part 28m 25s
Matplotlib, Seaborn, and Bokeh for Data Visualization: Introduction to Matplotlib7m 37s
Matplotlib, Seaborn, and Bokeh for Data Visualization: Seaborn Versus Matplotlib Style5m 33s
Matplotlib, Seaborn, and Bokeh for Data Visualization: Histograms Kdeplot12m 47s
Matplotlib, Seaborn, and Bokeh for Data Visualization: Seaborn Pairplot and Jointplot3m 27s
Matplotlib, Seaborn, and Bokeh for Data Visualization: Seaborn Pairplot using Iris Data6m 29s
Matplotlib, Seaborn, and Bokeh for Data Visualization: Introduction to Bokeh11m 7s
Matplotlib, Seaborn, and Bokeh for Data Visualization: Bokeh Gridplot5m 54s
Scikit-Learn for Machine Learning: Introduction to Scikit-Learn5m 25s
Scikit-Learn for Machine Learning: Scikit-Learn for Linear Regression6m 46s
Scikit-Learn for Machine Learning: Scikit-Learn for SVM and Random Forests15m 19s
Scikit-Learn for Machine Learning: Scikit-Learn - Trend Analysis COVID1910m 57s
Chapter 3 : Basics for Data Science: Data Understanding and Data Visualization with Python 10h 55m
Chapter 4 : Basics for Data Science: Mastering Probability and Statistics in Python 13h 38m
Chapter 5 : Machine Learning: Machine Learning Crash Course 9h 30m
Introduction9m 26s
Introduction: Python Practical of the Course6m 54s
Why Machine Learning: Machine Learning Applications-Part 19m 17s
Why Machine Learning: Machine Learning Applications-Part 29m 43s
Why Machine Learning: Why Machine Learning is Trending Now8m 53s
Process of Learning from Data: Supervised Learning10m 9s
Process of Learning from Data: Unsupervised Learning and Reinforcement Learning10m 42s
Machine Learning Methods: Features13m 21s
Machine Learning Methods: Features Practice with Python16m 49s
Machine Learning Methods: Regression4m 23s
Machine Learning Methods: Regression Practice with Python18m 17s
Machine Learning Methods: Classification4m 58s
Machine Learning Methods: Classification Practice with Python6m 5s
Machine Learning Methods: Clustering4m 33s
Machine Learning Methods: Clustering Practice with Python7m 18s
Data Preparation and Pre-processing: Handling Image Data7m 56s
Data Preparation and Preprocessing: Handling Video and Audio Data9m 36s
Data Preparation and Preprocessing: Handling Text Data9m 21s
Data Preparation and Preprocessing: One Hot Encoding19m 45s
Data Preparation and Preprocessing: Data Standardization14m 45s
Machine Learning Models and Optimization: Machine Learning Model 110m 28s
Machine Learning Models and Optimization: Machine Learning Model 213m 53s
Machine Learning Models and Optimization: Machine Learning Model 310m 9s
Machine Learning Models and Optimization: Training Process, Error, Cost and Loss9m 24s
Machine Learning Models and Optimization: Optimization13m 2s
Building Machine Learning Model from Scratch: Linear Regression from Scratch- Part 18m 16s
Building Machine Learning Model from Scratch: Linear Regression from Scratch- Part 215m 47s
Building Machine Learning Model from Scratch: Minimum-to-mean Distance Classifier from Scratch- Part 16m 51s
Building Machine Learning Model from Scratch: Minimum-to-mean Distance Classifier from Scratch- Part 28m 48s
Building Machine Learning Model from Scratch: K-Means Clustering from Scratch- Part 16m 13s
Building Machine Learning Model from Scratch: K-Means Clustering from Scratch- Part 217m 39s
Overfitting, Underfitting, and Generalization: Overfitting Introduction5m 54s
Overfitting, Underfitting, and Generalization: Overfitting Example in Python13m 25s
Overfitting, Underfitting, and Generalization: Regularization17m 13s
Overfitting, Underfitting, and Generalization: Generalization10m 28s
Overfitting, Underfitting, and Generalization: Data Snooping and the Test Set13m 5s
Overfitting, Underfitting and Generalization: Cross-validation11m 10s
Machine Learning Model Performance Metrics: The Accuracy6m 26s
Machine Learning Model Performance Metrics: The Confusion Matrix8m 15s
Dimensionality Reduction: The Curse of Dimensionality13m 2s
Dimensionality Reduction: The Principal Component Analysis (PCA)9m 36s
Deep Learning Overview: Introduction to Deep Neural Networks (DNN)9m 37s
Deep Learning Overview: Introduction to Convolutional Neural Networks (CNN)6m 10s
Deep Learning Overview: Introduction to Recurrent Neural Networks (CNN)9m 30s
Hands-on Machine Learning Project Using Scikit-Learn: Principal Component Analysis (PCA) with Python12m 58s
Hands-on Machine Learning Project Using Scikit-Learn: Pipeline in Scikit-Learn for Machine Learning Project11m 38s
Hands-on Machine Learning Project Using Scikit-Learn: Cross-validation with Python13m 52s
Hands-on Machine Learning Project Using Scikit-Learn: Face Recognition Project with Python34m 2s
OPTIONAL Section- Mathematics Wrap-Up: Mathematical Wrap-Up on Machine Learning41m 8s
Chapter 6 : Machine Learning: Feature Engineering and Dimensionality Reduction with Python 10h 52m
Chapter 7 : Deep learning: Artificial Neural Networks with Python 11h 50m
Chapter 8 : Deep learning: Convolutional Neural Networks with Python 11h 6m
Chapter 9 : Deep learning: Recurrent Neural Networks with Python 11h 17m
NumPy for Numerical Data Processing: Introduction to NumPy
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