Includes
 Duration: 3 months 29 days
 Chapters: 142
 Total Hours: 14:43 Hours
Features
 Full lifetime access
 Access on mobile
 Assignments
 Certificate of Completion
Overview
Course Description
Embarking on a transformative journey into the dynamic realm of Data Analytics and Visualization promises to equip participants with essential and soughtafter tech skills. This comprehensive course is meticulously designed to empower learners with proficiency in key tools and methodologies crucial for success in the field.
The primary learning objectives of this course include:
1. Python Proficiency: Participants will gain handson experience in Python, a versatile programming language widely used for data analysis and manipulation. Through practical exercises, learners will understand how to leverage Python libraries such as Pandas and NumPy for efficient data handling and manipulation.
2. Excel Mastery: Advanced skills in Excel will be developed, exploring its robust features for data organization, analysis, and visualization. Participants will harness the power of Excel functions and formulas to extract insights from complex datasets.
3. Statistical Foundations: A solid foundation in statistical concepts and techniques will be acquired, essential for making informed decisions based on data. Participants will learn to apply statistical methods to interpret and draw meaningful conclusions from datasets.
4. Data Analysis Process: The entire data analysis process will be explored, from data cleaning and preprocessing to exploratory data analysis (EDA) and feature engineering. Participants will learn how to identify patterns, outliers, and trends within datasets, enabling them to extract valuable insights.
5. Data Visualization: The art of presenting data visually will be mastered through a variety of visualization tools and techniques. Participants will use industrystandard tools like Matplotlib and Seaborn to create compelling and informative data visualizations.
Upon completion of the course, participants will possess a wellrounded skill set in data analytics and visualization. They will be equipped to tackle realworld challenges and contribute meaningfully to datadriven decisionmaking in any professional setting.
Joining this transformative journey promises to elevate participants into proficient and soughtafter tech professionals in the field of data analytics and visualization. With these skills, participants will be wellpositioned to excel in the everevolving landscape of data science and analytics.
What you'll learn
 Realworld use cases of Python and its versatility.
 Installation of Python on both Mac and Windows operating systems.
 Fundamentals of programming with Python, including variables and data types.
 Working with various operators in Python to perform operations.
 Fundamental concepts and importance of statistics in various fields.
 How to use statistics for effective data analysis and decisionmaking.
 Introduction to Python for statistical analysis, including data manipulation and visualization.
Requirements
 Students should have a general understanding of how to operate a computer.
 Be comfortable with common tasks like file management and using a web browser.
 No Prior Programming Experience Required.
 A basic understanding of mathematics, including algebra and arithmetic.
 Familiarity with fundamental concepts in data analysis and problemsolving.
Course Content
120 Lessons  3 Quiz  14:43 Hours
Excel Fundamentals

Excel Applications

Understanding the Excel Interface
00:16:41 
Sorting and Filtering
00:15:17 
Conditional Formatting
00:08:59 
Quiz on Excel Fundamentals
Statistical and Mathematical Functions in Excel

Introductions to Statistical Functions
00:09:39 
Introduction to Mathematical Functions
00:08:57 
Quiz on Statistical and Mathematical Functions
Lookup functions, and Pivot Tables

Introduction to Lookup Functions

Introduction to Index and Match
00:07:48 
Introduction to Pivot Tables
00:10:15 
Introduction to Pivot Charts

Quiz on Lookup Functions, and Pivot Tables
Logical Functions, and Text Functions

Introduction to Logical Function
00:06:35 
Formatting Cells based on Logical Functions
00:04:52 
Introduction to Text Functions
00:06:41 
Formatting cells based on Text Functions
00:09:21 
Quiz on Logical Functions, and Text Functions
Data Cleaning, and Feature engineering

Introduction to Date and Time Functions
00:07:11 
Basics of Data Cleaning in Excel
00:09:16 
Basics of Feature Engineering in Excel
00:07:13 
Introduction to Power Query in Excel
00:05:10 
Quiz on Data Cleaning and Feature Engineering
What If analysis

Scenario Manager
00:07:47 
Goal Seek
00:04:56 
Data Tables
00:17:35 
Solver Package

Quiz on What If analysis
Charts and Dashboards

Data Visualization Best Practices
00:09:11 
Types of Charts in Excel
00:04:54 
Creating and Formatting Charts
00:03:47 
Quiz on Charts and Dashboards
Linear Regression and Forecasting

Introduction to Linear Regression...
00:10:10 
Preliminary Forecasting Analysis....
00:06:50
Basics of Python

Real world use cases of Python

Installation of Anaconda for Windows and macOS
00:04:48 
Introduction to Variables
00:05:59 
Introduction to Data Types and Type Casting
00:06:27 
Scope of Variables
00:08:18 
Introduction to Operators
00:19:03 
Quiz on Basics of Python
Introduction to Data Structures

Introduction to Lists and Tuples

Introduction to Sets and Dictionaries
00:12:12 
Introduction to Stacks and Queues
00:06:57 
Introduction to Space and Time Complexity
00:13:27 
Introduction to Sorting Algorithms
00:08:36 
Introduction to Searching Algorithms
00:08:47 
Quiz on Data Structures
Introduction to Functions in Python

Introduction to Parameters and Arguments

Introduction to Python Modules
00:05:39 
Introduction to Filter, Map, and Zip Functions
00:13:44 
Introduction to List, Set and Dictionary Comprehensions
00:10:23 
Introduction to Lambda Functions
00:07:03 
Introduction to Analytical and Aggregate Functions
00:08:09 
Quiz on Functions in Python
Strings and Regular Expressions

Introduction to Strings
00:05:44 
Introduction to Important String Functions
00:10:46 
Introduction to String Formatting and User Input
00:08:30 
Introduction to Meta Characters
00:22:30 
Introduction to Builtin Functions for Regular Expressions
00:07:44 
Special Characters and Sets for Regular Expressions
00:07:30 
Quiz on Strings and Regular Expressions
Loops and Conditionals

Introduction to Conditional Statements
00:06:35 
Introduction to For Loops
00:04:18 
Introduction to While Loops

Introduction to Break and Continue
00:03:09 
Using Conditional Statements in Loops
00:05:51 
Nested Loops and Conditional Statements
00:07:10 
Quiz on Loops and Conditionals
OOPs and DateTime

Introduction to OOPs Concept
00:05:21 
Introduction to Inheritance

Introduction to Encapsulation
00:03:28 
Introduction to Polymorphism
00:05:23 
Introduction to Date and Time Class
00:07:53 
Introduction to TimeDelta Class
00:05:17 
Quiz on OOPs and DateTime
Introduction to Statistics

Explain the role of statistics in data analysis
00:05:22 
Introduction to Python for Statistical Analysis
00:05:31 
Introduction to Statistics and its importance
00:05:58 
Quiz on Introduction to Statistics
Introduction to Descriptive Statistics

Types of Data

Measures of Central Tendency
00:06:18 
Measures of Spread
00:04:37 
Measures of Dependence
00:05:06 
Measures of Shape and Position
00:09:37 
Measures of Standard Scores

Quiz on Descriptive Statistics
Introduction to Basic and Conditional Probability

Introduction to Basic Probability

Introduction to Set Theory
00:06:58 
Introduction to Conditional Probability
00:05:12 
Introduction to Bayes Theorem
00:08:23 
Introduction to Permutations and Combinations
00:07:47 
Introduction to Random Variables
00:05:25 
Introduction to Probability Distribution Functions
00:13:43 
Quiz on Basic and Conditional Probability
Introduction to Inferential Statistics

Introduction to Normal Distribution

Introduction to Skewness and Kurtosis
00:09:01 
Introduction to Statistical Transformations
00:12:46 
Introduction to Sample and Population Mean
00:04:57 
Introduction to Central Limit Theorem
00:05:08 
Introduction to Bias and Variance
00:07:28 
Introduction to Maximum Likelihood Estimation
00:06:53 
Introduction to Confidence Intervals
00:05:12 
Introduction to Correlations
00:18:27 
Introduction to Sampling Methods
00:17:00 
Quiz on Inferential Statistics
Introduction to Hypothesis Testing

Fundamentals of Hypothesis Testing
00:07:09 
Introduction to T Tests
00:09:00 
Introduction to Z Tests
00:05:37 
Introduction to Chi Squared Tests
00:15:16 
Introduction to Anova Tests
00:03:30 
Quiz on Hypothesis Testing
Introduction to Numpy and Pandas

Introduction to Numpy Arrays
00:08:10 
Introduction to Numpy Operations
00:12:38 
Introduction to Pandas
00:05:54 
Introduction to Series and DataFrames
00:11:02 
Reading CSV and JSON Data using Pandas
00:03:56 
Analyzing the Data using Pandas
00:03:21 
Quiz on Introduction to Numpy and Pandas
Advanced Functions in Pandas

Indexing, Selecting, and Filtering Data
00:14:54 
Merging and Concatenation using Pandas
00:07:29 
Correlation and Plotting using Pandas
00:09:30 
Introduction to Lambda, Map and Apply Functions
00:04:47 
Introduction to Grouping Operations using Pandas
00:08:59 
Introduction to Cross Tabulation using Pandas
00:03:46 
Introduction to Filtering Operations using Pandas
00:08:58 
Interactive Grouping and Filtering Operations
00:10:00 
Quiz on Advanced Functions in Pandas
Types of Charts and Visualizations

Factors for good Data Visualization

Introduction to Univariate Data Visualizations
00:09:10 
Introduction to Bivariate Data Visualizations
00:03:10 
Plotting two Categorical Variables
00:04:30 
Introduction to Multivariate Data Visualizations
00:04:29 
Introduction to Heatmaps and Pairplots
00:04:29 
Quiz on Types of Charts and Visualizations
Advanced Data Visualizations

Introduction to Animated Data Visualizations using Plotly
00:10:24 
Colorscales, Facet Grids, and Sub plots
00:22:30 
Introduction to 3D Data Visualization
00:06:56 
Introduction to Interactive Data Visualization
00:09:00 
Introduction to Maps using Plotly
00:07:49 
Introduction to Funnel and Gantt Charts using Plotly
00:14:07 
Quiz on Advanced Data Visualizations