Designed by the OK Google Developer, this course will help you master the most popular and highly-demanded programming language Python along with Data Structures and Machine Learning. Create your own Machine Learning applications by the end of this course.
This course includes important Data Science topics such as Data Collection, Data Visualization, Data Preprocessing, Machine Learning.
In this course you will learn the basics of Python Programming required for Data Science and Important Python Libraries required for Data Science.
After completing these modules you will learn how to use your knowledge of Data Science in Projects. This course includes Capstone Projects including Building a Movie Recommendation System, Cancer Prediction, etc.
Importance of Python
Describe the basics of the Python programming language
Install Python and write your first program
Use variables and constants to store, retrieve and calculate information
Utilize core programming tools such as functions and loops
Accomplish multi-step tasks like sorting or looping using tuples
Create programs that are able to read and write data from files
Store data as key/value pairs using Python dictionaries
Start with basics of Object Oriented Programming
Understanding class and object
Encapsulation, abstraction, inheritance and polymorphism
Using Scikit Learn in Machine Learning Techniques like Regression, Classification, Clustering, Recommender Systems
Doing basic project in Python
Select and process the data
Process data using Graphs Library in Python
Creating capstone project on Machine Learning using TensorFlow in Python
Usage of Python Libraries
Live Classes
Machine Learning
Introduction to the course
Need of Programming: What it takes to become a top notch programmer
Introduction to Python: Why it is the most demanded language and how tech giants are using it
Introduction to Python: Transition from Python 2 to Python 3
Instructions: Installation of Python on Windows and Mac
Demo: Step-by-step guide to installing Python on your PC
Python Usage: Introduction to practical use case of Python
Python Online: How to use your Machine to code online
Build your 1st Python code: Hello world assignment
Constants in Python: Introduction, application and use cases
Variable Reserved Words in Python: Introduction, application and use cases
Data Types in Python
Conversions in Python: Type and string conversions
Taking user inputs in Python: Introduction and application
Module Quiz: Constant Resever Words Variables
Module Assignment : Expressions and User Input
Using Comparison Operator in Python
Using IF ELIF Conditions in Python
Demo: Using conditions in Python
Using EXCEPT in Python
Demo: Using EXCEPT in Python
Module Quiz: Conditions and Comparisons
Module Assignment: TRY EXCEPT Assignment
Module Assignment Solution:TRY EXCEPT in Python
Understanding Functions in Python
Understanding Functions with Arguments in Python
Return Functions: Introduction and use cases
Multiple Arguments in Python: Introduction and use cases
Module Quiz: Functions in Python
Module Assignment: Functions in Python
Module Assignment Solution: Functions in Python
Loops in Python: Introduction
Break Continue: Understanding and Use Cases
FOR Loop: Understanding and Use Cases
Demo: Loops Code Implmentation
Loops and interation
Demo: Mastering Loops with more Use Cases
Module Quiz: Loops in Python
Module Assignment: Loops in Python
Module Assignment Solution: Loops in Python
Data Structures in Python: Course Introduction
Machine Learning in Python: Course Introduction
Python Interview Questions: Top 15 Python Programming Questions
Social Media Links for references
Introduction Video: Data Structures Course
Introduction to Strings and LEN function
String Looping: Introduction and Use Cases
String Slicing: Introduction and Use Cases
String Library Function: Introduction and Use Cases
Stripping Whitespace: Introduction and Use Cases
PARSING EXTRACTING
Module Quiz: Strings in Python
Module Assignment: Strings in Python
Module Assignment Solution: Strings in Python
Introduction to Files in Python
Counting Lines in a File in Python: Introduction and use cases
Reading files in Python: Introduction and use cases
Searching Lines in a File in Python: Introduction and use cases
Naming Files with User Data: Introduction and use cases
Module Quiz: Files in Python
Module Assignment: Handling files in Python
Module Assignment Solution: Handling files in Python
Introduction to Lists in Python
Finding Length of Range Objects in Python: len()
Continuation of lists and their use cases
Calculating Sum and Average of Lists in Python
Spliting Strings in to Lists in Python: split()
Moduel Quiz: Lists
Module Assignment: Lists in Python
Module Assignment Solution: Lists in Python
Understanding Dictionaries in Python
Distinguishing Lists and Dictionaries in Python: Lists Vs. Dictionaries
Demo: Understanding Get Function in Python
Iterating over dictionaries with loops
Module Quiz: Dictionaries in Python
Module Assignment: Dictionaries in Python
Module Assignment Solution: Dictionaries in Python
Understanding Tuples in Python
Distinguishing Tuples and Dictionaries in Python: Tuples Vs. Dictionaries
Sorting a Tuple in Python
Module Quiz: Tuples
Module Assignment: Tuples in Python
Module Assignment Solution: Tuples in Python
Uderstanding Sets in Python
Creating Sets in Python
Creating Empty Dictionaries in Python: Empty Set
Understanding Add and Update in Sets
Deleting Elements of Sets in Python
Distinguishing Sets, Lists and Dictionaries in Python: Sets Vs. Lists Vs. Dictionaries
Python Set Operations (Union, Intersection, Difference and Symmetric Difference)
Understanding Python Set Methods
Module Quiz: Sets in Python
Module Assignment: Python Sets
Machine Learning: Introduction
Social Media Links for references
Data Strcuture Interview Questions: Top Data Structure Programming Questions
Implementing Stacks and Queues
Searching, Sorting and Complexity Analysis in Data Structures
Understanding programming concepts in relation to OOPs
Distinguishing Procedural and OOPs: Procedural Programming Vs. Object Oriented Programming
Understanding Objects in OOPs
Understanding Classes in OOPs
Demo: Objects and Classes in OOPs
Understanding Constructors
Understanding Types of Constructors
Introduction to Encapsulation and Abstraction in Python
Use Cases of Encapsulation and Abstraction in Python
Understanding Inheritance in Python
Demo: Use Cases of Inheritance
Understanding Polymorphism in Python
Demo: Use Cases of Polymorphism
Various Functions in Inheritance and Polymorphism
Module Quiz: OOPs
Module Assignment : OOPs
Project: Red Wine - Predicting Qualtiy of Wines
Dealing with Missing Values in Python
Understanding Machine Learning: Use Case Scenarios
Project: Medical Cost Prediction
Python Libraries Guides
Matplotlib: Creating Static, Animated, and Interactive visualizations in Python
Pandas: Analysing Data in Python
*Args And **Kwargs: Passing a variable number of arguments to a Python function
NumPy: Working with Arrays in Python
Sets in Python
Python OOPs Concepts
Exploratory Data Analysis aka EDA on Red Wine Data - Part 2
Exploratory Data Analysis aka EDA on Red Wine Data - Part 1
Python Test Quiz
Tutorial - Seaboar
Python Projects - Stop Watch
H2O Tutorial - Machine Learning Framework
Various Types of Data Distribution
Various Types of Errors in Machine Learning Models
Course Walkthrough
Overview to Machine Learning
Artificial Intelligence Vs Machine Learning Vs Deep Learning
Machine Learning: Python Libraries
Supervised Vs. Unsupervised Learning
Module Quiz: Machine Learning Overview
Introduction to Regression
Various Regression Techniques: Linear, Polynomial, Stepwise, Ridge, Lasso and ElasticNet
Linear Regression using Python
Linear Regression Techniques: Slopes And Intercept
Linear Regression using SKLEARN Coding
Demo Machine Code: Linear Regression using SKLEARN Coding
Demo Code Explaination: Linear Regression using SKLEARN Coding
Errors in Linear Techniques
R-Squared or Coefficient of Determination
Multiple Linear Regression (MLR)
Polynomial Vs. Non Linear Regression
Module Quiz: Regression in Python
Introduction to Classification
K-Nearest Neighbor(KNN) Algorithm for Machine Learning Introduction
Working with K-Nearest Neighbor(KNN) Algorithm for Machine Learning
Evaluation Metrics for Classification
Machine Learning Decision Tree Classification Algorithm
Support Vector Machine (SVM) Algorithm in Machine Learning
Machine Learning Random Forest Algorithm
Module Quiz: Classification
Clustering Algorithms in Machine Learning
Clustering Vs Classifications: Machine Learning
K means Clustering - Introduction
Module Quiz: Clusterin in Machine Learning
Understanding Recommender Systems in Machine Learning
Content-based Filtering: Recommendation Systems
Collaborative Filtering: Recommendation Systems
Module Quiz: Recommender Systems in Machine Learning
Introduction to the Project: Guess Game
Project Implementation: Undestanding the Concepts to Build Guess Game
Proejct Code: Guess Game Using Python
Understanding Python Libraries
Three-dimensional Plotting in Python using Matplotlib
Tri-Surface Plot in Python using Matplotli
Professional 3D Plotting in Matplotlib - 3D Plot Game
Understanding Machine Learning Concepts
Flowcharts - Problem Solving with Python
Deep Learning: Training and Testing the Network with Tensorflow and Keras
Tensorflow and Keras For Neural Networks and Deep Learning
Final Certification Quiz; Complete Course
Machine Learning Final Assignment
Machine Learning Live Class with Google Expert
Logistic Regression for Malignancy Prediction in Cancer (Breast Cancer)
Spam Mail Prediction using Machine Learning with Python
Personal Assistant
Weather recommendation system
Understanding Machine Learning Workflow
Decoding Model Selection for Machine Learning
Understanding Overfitting in Machine Learning
Understanding Underfitting in Machine Learning
Understanding the Bias-Variance Tradeoff
Introduction to Dimensionality Reduction for Machine Learning
Gradient Descent algorithm and its Variants
Hands-On-Guide To Machine Learning Model Deployment Using Flask
GitHub Tutorial and Profile Buidling
Course Introduction
Course Curriculum
Overview of the steps involved
Understanding the problem statement
Data Collection
Data Visualization and Analysis
Data Preprocessing - Part 1
Data Preprocessing - Part 2
Model Selection
Evaluation
Presenting our Insights
Summary
Module 2 : Steps involved in a Data Science Project
Overview
Google Colaboratory - Getting Started
Google Colab - Basics
Python Basics - Synopsis
Python Basics
Basic Python Data Types
Basic Operators in Python
Special Data Types - list
Tuple, Set and Dictionary
If Statements
Loops
Module 4 : Python Basics
Assignment 1 - Python basics
Overview
Numpy Basics Part - 1
Numpy Basics Part - 2
Numpy Basics - Part 3
Pandas Basics - Part 1
Pandas Basics - Part 2
Other important Python Libraries
Module 5 : Numpy and Pandas Tutotial
Assignment 2 - Pandas and Numpy Tutorial
Data Collection - Overview
Getting the dataset - part 1
Getting the dataset - part 2
Importing Kaggle Dataset through API
Web Scrapping - Wikipedia Table
Summary
Assignment 3 - Data Collection
Data Visualization - Overview
Data Visualization - Example
Basic Plots - Matplotlib
Iris Dataset - Visualization
Titanic Dataset - Visualization
Module 7 : Data Visualization and Analysis
Assignment 4 - Data Visualization and Analysis
Data Preprocessing - Overview
Dataset Manipulation - Basics
Handling missing values - by Dropping
Handling missing values - by Imputation
Dataset Standardization
Label Encoding
Module 8: Data Pre-processing
Assignment 5 - Data pre-processing
Overview
AI vs ML vs DL
Machine Learning
Types of Machine Learning
Model Selection
9.6. Logistic Regression model
Support Vector Machine model
Module 9 : Machine Learning - Basics
Data Science Projects - Overview
Breast Cancer Prediction - Overview
Breast Cancer Prediction - Logistic Regression - Part 1
Breast Cancer Prediction - Part 2
Iris Clustering
Spam mail prediction
Movie Recommendation System - Overview
Movie Recommendation System - Part 1
Movie Recommendation System - Part 2
Assignment 6 - Data Science projects
Introduction - Overleaf, Online LaTeX Editor
Building Professional/Educational Resume using LaTeX
The course has been designed by the Perfect Plan B Mentor team. Our mentors are alumni of NIT & IIT with 8+ years of industry experience working with Google, Adobe and Flipkart.
We at Perfect Plan B are working towards eradicating the financial hurdles from education with our Learn Now, Pay Later initiative. This course will not only help you in getting industry specific knowledge but will also help you achieve your career goals with right training and mentoring from P2B team.
$388.00
853.00
₹28,300.00
62,300.00
Lifetime Video Access
Certificate of Completion
Approx. 3 Months to Complete
Live Classes
Quizzes and Assignments
No Prior Experience Required
Top 50 Interview Question
Resume Building
Internships and Placement
