Master Advanced Data Analytics by solving Real-Life Analytics Problems using Python. Learn by doing!
What you will learn
Learn about python variables and data types.
Learn about loops and conditionals in python.
Learn about the different data structures of python.
Learn about the creation of functions in python.
Learn about object oriented programming using python.
Learn about searching, sorting and time complexity in python.
Learn about Regular expressions and date time objects in Python.
Learn about the Numpy and the Pandas library.
Learn exploring data using Dabl and Sweetviz library.
Learn probability concepts such as Conditional probability, bayes theorem.
Learn about descriptive and inferential statistics.
Learn the concept of normal distribution.
Learn about the different hypothesis tests- T test, Z test, Anova Test and Chi Squared test
Learn about the different hypothesis tests- T test, Z test, Anova Test and Chi Squared test.
Learn how to handle missing values and outliers.
Learn the basics as well as advanced visualization techniques.
Learn how to use of group by functions, pivoting functions.
Quizzes and exercises
Use Python to solve real-world tasks
Learn how to code in Python
Learn to program in Python at a good level
Description
Welcome to the online course on Advanced Data Analytics using Python.
Data analysts exist at the intersection of information technology, statistics and business. They combine these fields in order to help businesses and organizations succeed.
The primary goal of a data analyst is to increase efficiency and improve performance by discovering patterns in data.
In this course, you will get advanced knowledge on Data Analytics.
This course begins with providing you the complete knowledge on Python programming language.
You will learn all the concepts of python programming from basics to advanced level.
This course will cover the following topics:-
- Variables and data types
- Loops and conditionals
- Functions
- Object oriented programming
- Dates and times
- Regular expressions
- Numpy and pandas library
Along with python programming, this course will cover other data analytics concepts such as
- Data Visualization
- Data cleaning
- Query Analysis
- Data Exploration
- Statistics and Probability concepts
All these topics are covered in detail.
Along with theory you will get to practice them using some real world datasets.
There will be lots of exercises and quizzes.
Not only this, you will get to work on some exciting projects including Startups Case Study and Analysis, IPL Player performance Analysis.
Instructor Support – Quick Instructor Support for any queries.
I’m looking forward to see you in the course!
Lots of exercises and quizzes are waiting for you.
You will also have access to all the resources used in this course.
Enroll now and become an expert in data analytics.
English
language
Content
Python Fundamentals
Introduction
Why should you learn Python?
Installing Python and Jupyter Notebook
Understanding the Interface of Jupyter Notebook
Naming Convention for variables
Built in Data Types and Type Casting
Scope of Variables
Quiz on Variables and Data Types
Quiz Solution
Exercise on Variables and Data Types
Solution on Variables and Data Types
Exercise on Scope of Variables
Solution on Scope of Variables
Arithmetic and Assignment Operators
Comparison, Logical, and Bitwise Operators
Identity and Membership Operators
Quiz on Operators
Quiz Solution
Exercise on Arithmetic and Assignment Operators
Solution on Arithmetic and Assignment Operators
Exercise on Comparison, Logical, and Bitwise Operators
Solution on Comparison, Logical, and Bitwise Operators
Exercise on Identity and Membership Operators
Solution on Identity and Membership Operators
String Formatting
String Methods
User Input
Quiz on Strings
Quiz Solution
Exercise on Strings
Solution on Strings
If, elif, and else
For and While
Break and Continue
Quiz on Loops and conditionals
Quiz Solution
Exercise on Loops and Conditionals
Solution on Loops and Conditionals
Python Data Structures
Differences between Lists and Tuples
Operations on Lists
Operations on Tuples
Quiz on Lists and Tuples
Quiz Solution
Exercises on Lists
Solution on Lists
Introduction to Dictionaries
Operations on Dictionaries
Nested Dictionaries
Introduction to Sets
Set Operations
Quiz on Sets and Dictionaries
Quiz Solution
Exercise on Sets
Solution on Sets
Exercises on Dictionaries
Solution on Dictionaries
Introduction to Stacks and Queues
Implementing Stacks and Queues using Lists
Implementing Stacks and Queues using Deque
Quiz on Stacks and Queues
Quiz Solution
Exercise on Stacks and Queues
Solution on Stacks and Queues
Time Complexity
Linear Search
Binary Search
Bubble Sort
Insertion and Selection Sort
Merge Sort
Quiz on Searching, Sorting, and Time Complexity
Quiz Solution
Exercise on Searching and Sorting
Solution on Searching and Sorting
Exercise on Time Complexity
Solution on Time Complexity
Python Functions Deepdive
Introduction to Functions
Default Parameters in Functions
Positional Arguments
Keyword Arguments
Python Modules
Quiz on Introduction to Functions
Quiz Solution
Exercises on Functions
Solution on Functions
Exercises on Modules
Solution on Modules
Lambda Functions
Filter, Map, and Zip Functions
List, set, and Dictionary Comprehensions
Quiz on Anonymous Functions
Quiz Solution
Exercise on Lambda Functions
Solution on Lambda Functions
Exercise on Filter, Map, and Zip Functions
Solution on Filter, Map, and Zip Functions
Exercise on Comprehensions
Solution on Comprehensions
Introduction to Aggregate Functions
Introduction to Analytical Functions
Quiz on In Built Functions
Quiz Solution
Exercise on Aggregate Functions
Solution on Aggregate Functions
Exercise on Analytical Functions
Solution on Analytical Functions
Solving the Factorial Problem using Recursion
Solving the Fibonacci Problem using Recursion
Quiz on Recursions
Quiz Solution
Exercise on Recursions
Solution on Recursions
Introduction to Classes and Objects
Inheritance
Encapsulation
Polymorphism
Quiz on Classes and Objects
Quiz Solution
Exercise on Classes and Objects
Solution on Classes and Objects
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
Exercise on Date and Time
Solution on Date and Time
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
Exercise on Regular Expressions
Solution on Regular Expressions
Array Creation using Numpy
Mathematical Operations using Numpy
Built-in Functions in Numpy
Quiz on Introduction to Numpy
Quiz Solution
Exercise on Built-in Functions in Numpy
Solution on Built-in Functions in Numpy
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
Exercise on Pandas Plotting
Solution on Pandas Plotting
Exercise on Indexing and Selecting
Solution on Indexing and Selecting
Exercise on Apply Functions
Solution on Apply Functions
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
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 Probability
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 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
Data Visualization
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
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
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
Quiz on Startups case study and analysis
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
Analyzing 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
Players Performance Analysis
Understanding the problem statement
Setting up the Environment
Data Cleaning
Feature Engineering
Data Visualization
Query Analysis
Major Learnings from the project
Quiz on Players Performance Analysis
Outro Section
Conclusion
How to Get Your Certificate of Completion
Bonus Section
Bonus Lecture