Data Science Bootcamp 2022: 5 Data Science Projects

Data Science and Machine Learning Masterclass with Python with 5 Data Science Real World Projects

4.25 (760 reviews)
Udemy
platform
English
language
Data Science
category
39,633
students
15.5 hours
content
Apr 2022
last update
$74.99
regular price

What you will learn

Fundamentals of Data Science

Data Science Capstone Projects

Grouping and Filtering Operations for Data Analysis

Object Oriented Programming in Python

Hypothesis Testing

Basic and Advanced Data Visualization

Clustering Analysis

Description

Data Science is an interdisciplinary field that uses scientific methods, algorithms to extract clean information from raw data for the formulation of actionable insights.

The Data Science field is growing so rapidly, and revolutionizing so many industries.

Data Science has incalculable benefits in business, research, and our everyday lives.

Your route to work, your most recent Google search for the nearest coffee shop, your Instagram post about what you ate, and even the health data from your fitness tracker are all important to different data scientists in different ways.

Sifting through massive lakes of data, looking for connections and patterns, data science is responsible for bringing us new products, delivering breakthrough insights, and making our lives more convenient.


It encompasses a wide range of topics:-

  • Fundamentals of Python.

  • Python Data Structures.

  • Python Functions.

  • Python for Data Science.

  • Data Cleaning.

  • Query Analysis.

  • Data Visualizations using Python.

  • Statistics and Probability.

  • Hypothesis Testing.

  • Data Exploration.


Each of these topics are build on the other. You need to acquire all the skills in the right order.


You are at the right place!!!


Welcome to this online resource to learn Data Science Skills.

The Complete Data Science Bootcamp course will really help you to boost your career.

This Data Science Course begins with the most basic level and goes up to the most advanced techniques step by step.

even if you don't know anything in advance, this course will make complete sense to you.

In this  Data Science Course you will learn about the following:-

1. The fundamentals of python programming language:- variables, data types, loops and conditionals.

2. Python data structures:- lists, tuples, dictionaries, sets, stacks, queues.

3. Object-oriented programming in python.

4. Regular Expressions.

5. Numpy library.

6. Pandas library.

7. Grouping and filtering operations for data analysis.

8. Basic and Advanced visualizations.

9. Descriptive statistics.

10. Inferential statistics.

11. Hypothesis Testing.

12. Exploring Dabl and Sweetviz library.

13. Linear Regression theory and practical.

14. Logistic Regression theory and practical.

15. Clustering analysis.


There are lots and lots of exercises for you to practice In this Python Data Science Course and also a  5 Bonus Data Science Project "Player’s Performance Reviewer", "Start-ups Case Study and Analysis", "Movie Recommender Engine", "Global Cost of Living Analysis" and "Customer Segmentation Engine".

In this Player’s Performance Reviewer project, you will analyze the performance metrics of players based on their ground positions, skills, nationality, clubs, age, height, weight, and understanding the major factors driving the performance of these players.

In this Start-ups Case Study and Analysis project, you will analyze the Indian Startups, and Understand the Startup Ecosystems in India to answer some Interesting Questions. Try to find out the Major Investors and Startups.

In this Movie Recommender Engine project, you will get to learn How to analyze a Movie Database to find some useful insights and Recommend Movies.

In this Global Cost of Living Analysis project, you will learn how to perform Geospatial Analysis and understand some major factors determining the quality of life in different cities of the world. And also learn to perform Comparative analysis.

In this Customer Segmentation Engine project, you will divide the customer base into several groups of individuals that share a similarity in different ways that are relevant to marketing such as gender, age, interests, and miscellaneous spending habits.


You will make use of all the topics read in this Python Data Science Course 2021.

You will also have access to all the resources used in this Python Data Science Course 2021.

Instructor Support - Quick Instructor Support for any queries.


Enroll now and become a Data Science professional!!!

Content

Python Fundamentals

Why should you learn Python?
Installing Python and Jupyter Notebook
Naming Convention for variables
Built in Data Types and Type Casting
Scope of Variables
Quiz on Variables and Data Types
Quiz Solution
Arithmetic and Assignment Operators
Comparison, Logical, and Bitwise Operators
Identity and Membership Operators
Quiz on Operators
Quiz Solution
String Formatting
String Methods
User Input
Quiz on Strings
Quiz Solution
If, elif, and else
For and While
Break and Continue
Quiz on Loops and Conditionals
Quiz Solution

Python for Data Analysis

Differences between Lists and Tuples
Operations on Lists
Operations on Tuples
Quiz on Lists and Tuples
Quiz Solution
Introduction to Dictionaries
Operations on Dictionaries
Nested Dictionaries
Introduction to Sets
Set Operations
Quiz on Sets and Dictionaries
Quiz Solution
Introduction to Stacks and Queues
Implementing Stacks and Queues using Lists
Implementing Stacks andd Queues using Deque
Quiz on Stacks and Queues
Quiz Solution
Time Complexity
Linear Search
Binary Search
Bubble Sort
Insertion and Selection Sort
Merge Sort
Quiz on Searching, Sorting, and Time Complexity
Quiz Solution

Python Functions Deep Dive

Introduction to Functions
Default Parameters in Functions
Positional Arguments
Keyword Arguments
Python Modules
Quiz on Introduction to Functions
Quiz Solution
Lambda Functions
Filter, Map, and Zip Functions
List, set, and Dictionary Comprehensions
Quiz on Anonymous Functions
Quiz Solution
Introduction to Aggregate Functions
Introduction to Analytical Functions
Quiz on In Built Functions
Quiz Solution
Solving the Factorial Problem using Recursion
Solving the Fibonacci Problem using Recursion
Quiz on Recursions
Quiz Solution
Introduction to Classes and Objects
Inheritance
Encapsulation
Polymorhism
Quiz on Classes and Objects
Quiz Solution

Python for Data Science

Introduction to datetime
The date and time class
The datetime class
The timedelta class
Quiz on Dates and Times
Quiz Solution
Meta Characters for Regular Expressions
Built-in Functions for Regular Expressions
Special Characters for Regular Expressions
Sets for Regular Expressions
Quiz on Regular Expressions
Quiz Solution
Array Creation using Numpy
Mathematical Operations using Numpy
Built-in Functions in Numpy
Quiz on Introduction to Numpy
Quiz Solution
Reading Datasets using Pandas
Plotting Data in Pandas
Indexing, Selecting, and Filtering Data using Pandas
Merging and Concatenating DataFrames
Lambda, Map, and Apply Functions
Quiz on Introduction to Pandas
Quiz Solution

Data Cleaning

Causes and Impact of Missing Values
Types of Missing Values
When should we delete the missing values
Imputing missing values with the business logic
Imputing missing values with Mean/Median/Mode
Imputing missing values in a real-time scenario
Quiz on Missing Values Imputation
Quiz Solution
How outliers can be harmful for machine learning models
Finding out outliers from the data
Using Winsorization to deal with outliers
Deleting and Capping the outliers
Dealing with outliers in a real-world scenario
Quiz on Outliers Treatment
Quiz Solution
Introduction to reindex, set_index, reset_index, and sort_index Functions
Introduction to Replace and Drop level Function
Introduction to Split and Strip Function
Introduction to Stack, and Unstack Functions
Introduction to Melt, Explode, and Squeeze Functions
Data Cleaning on Big Mart Dataset
Data Cleaning on Movie Dataset
Data Cleaning on Melbourne Housing Dataset
Data Cleaning on Naukri Dataset

Query Analysis

Aggregate functions used for Grouping
Using Groupby for Grouping Operations
Groupby with Idxmax and Idxmin functions
Using Color scales for better visualization
Visualizing the Groupby Operations
Using Pivot Tables for Grouping Operations
Difference between Groupby and Pivot tables
Performing Cross Tabulation
Visualizing Cross tabulated Data
Interactive Grouping Operations
Quiz on Grouping Operations
Quiz Solution
When to perform Filtering Operations
Introduction to Simple Filtering Operations
Advanced Filtering Operations
Filtering and Grouping Operations
Interactive Filtering Operations
Quiz on Filtering Operations
Quiz Solution

Data Visualizations

Univariate Analysis
Bivariate Analysis
Multivariate Analysis
Quiz on Basics of Visualization
Quiz Solution
Scatter Plots
Charts with Colorscale
Bar, Line, and Area Charts
Facet Grids
Statistical Charts
Polar Charts
Subplots
3D Charts
Waffle Charts
Maps
Quiz on Advanced Visualizations
Quiz Solution
Animation with Bubbleplot
Animation with Facets
Animation with Scatter Maps
Animation with Choropleth Maps
Quiz on Animated Visualizations
Quiz Solution
Introduction to Ipywidgets
Interactive Univariate Analysis
Interactive Bivariate Analysis
Interactive Multivariate Analysis
Quiz on Interactive Visualizations
Quiz Solution
Sunburst Charts
Parallel Co-ordinate Charts
Funnel Charts
Gantt Charts
Ternary Charts
Tree Maps
Network Charts
Quiz on Miscellaneous Charts
Quiz Solution

Statistics and Probability

Why you should learn Statistics and Probability
Walking through the course Content
Applications of Probability in Real Life
Basic Probability
Conditional Probability
Set Theory
Bayes' Theorem
Permutations and Combinations
Quiz on Probablity
Quiz Solution
Types of Data
Measures of Central Tendency
Measures of Spread
Measures of Dependence
Quiz on Descriptive Statistics
Quiz Solution
Continuous vs Discrete Distributions
Introduction to Normal Distribution
Concept of Skewness
Using QQ Plots to check Normal Distribution
Quiz on Statistical Distributions
Quiz Solution
Sample Mean and Population Mean
Central Limit Theorem
Bias and Variance
Maximum Likelihood Estimation
Confidence Intervals
Quiz on Inferential Statistics
Quiz Solution

Hypothesis Testing

What is Hypothesis Testing
Null Hypothesis and Alternate Hypothesis
Types of Error
P-Value and Level of Significance
Quiz on Hypothesis Testing
Quiz Solution
One Sampled T Test
Two Sampled T Test
Paired Sampled T Test
Quiz on Student's T Test
Quiz Solution
One Sampled Z Test
Two Sampled Z Test
Quiz on Z Test
Quiz Solution
One Sampled ANOVA Test
Two Sampled ANOVA Test
Quiz on ANOVA Test
Quiz Solution
Goodness of Fit Test
Test of Independence
Quiz on Chi Squared Test
Quiz Solution

Data Exploration

Why EDA and how it is useful
Course curriculum walkthrough
Data Profiling
Analyzing Target Data
Quiz on Introduction to EDA
Quiz Solution
Summarizing data
Exploring the Dabl Library
Exploring the Sweetviz Library
Using Color Gradients for better analysis
Best Practices for Data Exploration
Quiz on Examining Data
Quiz Solution

Capstone Project 1: Players Performance Analysis

Understanding the problem statement
Setting up the Environment
Data Cleaning
Feature Engineering
Data Visualization
Query Analysis
Major Learnings from the project

Capstone Project 2: Startups Case Study and Analysis

Understanding the Problem Statement
Setting up the Environment
Data Cleaning
Querying the data using Visualizations Part - 1
Querying the data using Visualizations Part - 2
Major learning from the Project

Capstone Project 3: Movie Recommender Systems

Setting up the Environment
Taking a Deep Dive into the Dataset
Understanding the Problem Statement
Missing Values Imputation
Top 10 Profitable Movies
Manipulating the Duration and Language Column
Extracting the Movie Genres
Top 10 Most Popular Movies on Social Media
Analysing Which Genre is Most Bankable?
Loss and Profit Analysis on English and Foreign Movies
Gross Comparison of Long and Short Movies
Association between IMDB Rating and Duration
Comparing Critically acclaimed Actors
Top Movies based on Gross, and IMDB
Recommending Movies based on Languages and Actors
Recommending Similar Genres and Movies
Key Takeaways from this Project
Quiz on Movie Recommender Systems

Capstone Project 4: Global Cost of Living

Setting up Environment
Understanding the Dataset
Understanding the Problem Statement
Extracting Latitude and Longitude from the L
Performing Feature Engineering
Comparing Lifestyle in different Countries
Top N and Bottom N Analysis
Performing Geo spatial Analysis
Comparing different Lifestyle Factors
Comparing Some of the Most Popular Countries
Comparing Lifestyle in Indian Cities
Ranking Places based on their cost of living
Analysing Cost of Essential Items
Analysing Quality of Life
Suggesting Better places to live
Quiz on Global Cost of Living

Capstone Project 5: Customer Segmentation Engine

Understanding the Problem Statement
Setting up the Environment
Data Analysis and Visualization
KMeans Clustering Analysis
Major Learnings from the projects
Quiz on Customer Segmentation Engine

Screenshots

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Reviews

Jayanta
December 23, 2022
It's a great course. Everything is detailed oriented. It will enhance my skill and knowledge. Thanks & Best wishes to You.
Binu
October 27, 2022
The course is very good. I liked the Visualization section. There are some new tips and plots there. I would urge you to make more such courses that have something different from other courses available on the udemy.
Jatin
October 10, 2022
I really love this course! I have no experience in Data Science or Machine Learning, and through this course, I have basic knowledge of Data Science and Machine Learning. Thank you for providing this course. And I really appreciate the efforts. The course was more useful than I expected. Very interesting course with many important topics in Data Science. And the instructor is very explanatory and highly recommended.
Shubham
September 20, 2022
if you really want to brush up your python or if are a beginner then this course is for u which covers the python as well as the basics of data scientist and data analysis ...
Arun
July 28, 2022
Great course. It is awesome how deeply topics are covered and also difficult topics are made easy by the Instructors. The exercises are good to reinforce the knowledge. It covers almost every topic needed to get into the data science field. The lectures are well made and easy to understand. Thanks for the effort!
Sanket
July 6, 2022
This course is the best option for me because I have always been looking to do a course in Data Science with Python. This course is well structured and will make you understand data science step by step. I highly recommend this course for those who want to learn data science from basics to advanced.
Shivam
June 26, 2022
Really an Interesting course. Great opportunity to learn many data science concepts. The instructors did an amazing job in explaining difficult probability, statistics, and machine learning terms using suitable examples.
Ademola
April 17, 2022
It has been well-taken step by step so far. The course is detailed, and I hope it will be that way till the end. I appreciate the course intro.
José
April 12, 2022
Muy detallista al explicar todo. Pero no sé porqué hacen la encuesta al inicio del curso, pienso que debería ser al final.
Narendra
April 4, 2022
need to focus more explanation in Algorithms explanation, on statistics, Baye's Theorem, Regression topics is missing, Timeseries prediction to be covered,
Vijay
March 26, 2022
There is literally zero explanation about the syntax in data cleaning module and many more, it seems like you are just dictating context in display, what a waste of time and money.
Benedict
March 14, 2022
Reading just from the PowerPoint presentation without explanation is an inappropriate way to conduct course. I, as a beginner, find it difficult to understand concepts and solutions after the unit. You give the solution, but not the explanation.
Thomas
February 20, 2022
It's a well structured course and good for practice but I wasn't the biggest fan of the learning approach. The instructor reads every syntax out loud instead of going more into explanations and examples. At some point it becomes sort of "really you just gonna read the whole thing again?". Also I highly recommend you to add several code challenges to each chapter. For users who already have some python knowledge and are looking for a data science specific crash course I can recommend the course though.
Ricardo
January 25, 2022
The beggining was ok, but in the projects section some projects have multiple errors and I followed the exact steps in the class but the code gave me errors always. I asked for help to solve this but no one replied in one month. I was expecting to do the projects but it is not possible if the code provided it's wrong.
Prateek
January 23, 2022
There are a lot of mistakes in the explanation of concepts. Like in the OOPs part, the private, public and protected accessibility is not correctly explained. Also I found errors in a quiz.

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3914646
udemy ID
3/15/2021
course created date
4/29/2021
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