Embark on a transformative journey into the dynamic realm of Data Analytics and Visualization, where you will acquire essential and sought-after tech skills. This comprehensive course is designed to empower you with proficiency in key tools and methodologies, including Python programming, Excel, statistical analysis, data analysis, and data visualization.
Key Learning Objectives:
– Gain hands-on experience in Python, a powerful and versatile programming language widely used for data analysis and manipulation.
– Learn to leverage Python libraries such as Pandas and NumPy for efficient data handling and manipulation.
– Develop advanced skills in Excel, exploring its robust features for data organization, analysis, and visualization.
– Harness the power of Excel functions and formulas to extract insights from complex datasets.
– Acquire a solid foundation in statistical concepts and techniques essential for making informed decisions based on data.
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– Apply statistical methods to interpret and draw meaningful conclusions from data sets.
– Explore the entire data analysis process, from data cleaning and preprocessing to exploratory data analysis (EDA) and feature engineering.
– Learn how to identify patterns, outliers, and trends within datasets, enabling you to extract valuable insights.
– Master the art of presenting data visually through a variety of visualization tools and techniques.
– Use industry-standard tools like Matplotlib and Seaborn to create compelling and informative data visualizations.
Upon completion, you will possess a well-rounded skill set in data analytics and visualization, equipping you to tackle real-world challenges and contribute meaningfully to data-driven decision-making in any professional setting. Join us on this journey to become a proficient and sought-after tech professional in the field of data analytics and visualization.
Fundamentals of Excel
Excel Applications
Understanding the Excel Interface
Sorting and Filtering
Conditional Formatting
Quiz on Excel Fundamentals
Statistical and Mathematical Functions in Excel
Introductions to Statistical Functions
Introduction to Mathematical Functions
Quiz on Statistical and Mathematical Functions
Lookup functions, and Pivot Tables
Introduction to Lookup Functions
Introduction to Index and Match
Introduction to Pivot Tables
Introduction to Pivot Charts
Quiz on Lookup Functions, and Pivot Tables
Logical Functions, and Text Functions
Introduction to Logical Function
Formatting Cells based on Logical Functions
Introduction to Text Functions
Formatting cells based on Text Functions
Quiz on Logical Functions, and Text Functions
Data Cleaning, and Feature engineering
Introduction to Date and Time Functions
Basics of Data Cleaning in Excel
Basics of Feature Engineering in Excel
Introduction to Power Query in Excel
Quiz on Data Cleaning and Feature Engineering
What If analysis
Scenario Manager
Goal Seek
Data Tables
Solver Package
Quiz on What If analysis
Charts and Dashboards
Data Visualization Best Practices
Types of Charts in Excel
Creating and Formatting Charts
Quiz on Charts and Dashboards
Basics of Python
Real world use cases of Python
Installation of Anaconda for Windows and macOS
Introduction to Variables
Introduction to Data Types and Type Casting
Scope of Variables
Introduction to Operators
Quiz on Basics of Python
Introduction to Data Structures
Introduction to Lists and Tuples
Introduction to Sets and Dictionaries
Introduction to Stacks and Queues
Introduction to Space and Time Complexity
Introduction to Sorting Algorithms
Introduction to Searching Algorithms
Quiz on Data Structures
Introduction to Functions in Python
Introduction to Parameters and Arguments
Introduction to Python Modules
Introduction to Filter, Map, and Zip Functions
Introduction to Lambda Functions
Introduction to List, Set and Dictionary Comprehensions
Introduction to Analytical and Aggregate Functions
Quiz on Functions in Python
Strings and Regular Expressions
Introduction to Strings
Introduction to Important String Functions
Introduction to String Formatting and User Input
Introduction to Meta Characters
Introduction to Built-in Functions for Regular Expressions
Special Characters and Sets for Regular Expressions
Quiz on Strings and Regular Expressions
Loops and Conditionals
Introduction to Conditional Statements
Introduction to For Loops
Introduction to While Loops
Introduction to Break and Continue
Using Conditional Statements in Loops
Nested Loops and Conditional Statements
Quiz on Loops and Conditionals
OOPs and Date-Time
Introduction to OOPs Concept
Introduction to Inheritance
Introduction to Encapsulation
Introduction to Polymorphism
Introduction to Date and Time Class
Introduction to TimeDelta Class
Quiz on OOPs and Date-Time
Statistics and Hypothesis Testing for Data science
Introduction to Statistics and its importance
Explain the role of statistics in data analysis
Introduction to Python for Statistical Analysis
Quiz on Introduction to Statistics
Statistics and Hypothesis Testing for Data science
Types of Data
Measures of Central Tendency
Measures of Spread
Measures of Dependence
Measures of Shape and Position
Measures of Standard Scores
Quiz on Descriptive Statistics
Introduction to Basic and Conditional Probability
Introduction to Basic Probability
Introduction to Set Theory
Introduction to Conditional Probability
Introduction to Bayes Theorem
Introduction to Permutations and Combinations
Introduction to Random Variables
Introduction to Probability Distribution Functions
Quiz on Basic and Conditional Probability
Introduction to Inferential Statistics
Introduction to Normal Distribution
Introduction to Skewness and Kurtosis
Introduction to Statistical Transformations
Introduction to Sample and Population Mean
Introduction to Central Limit Theorem
Introduction to Bias and Variance
Introduction to Maximum Likelihood Estimation
Introduction to Confidence Intervals
Introduction to Correlations
Introduction to Sampling Methods
Quiz on Inferential Statistics
Introduction to Hypothesis Testing
Fundamentals of Hypothesis Testing
Introduction to T Tests
Introduction to Z Tests
Introduction to Chi Squared Tests
Introduction to Anova Tests
Quiz on Hypothesis Testing
Data Analysis and Data Viz : Introduction to Numpy and Pandas
Introduction to Numpy Arrays
Introduction to Numpy Operations
Introduction to Pandas
Introduction to Series and DataFrames
Reading CSV and JSON Data using Pandas
Analyzing the Data using Pandas
Quiz on Introduction to Numpy and Pandas
Advanced Functions in Pandas
Indexing, Selecting, and Filtering Data
Merging and Concatenation using Pandas
Correlation and Plotting using Pandas
Introduction to Lambda, Map and Apply Functions
Introduction to Grouping Operations using Pandas
Introduction to Cross Tabulation using Pandas
Introduction to Filtering Operations using Pandas
Interactive Grouping and Filtering Operations
Quiz on Advanced Functions in Pandas
Types of Charts and Visualizations
Factors for good Data Visualization
Introduction to Univariate Data Visualizations
Introduction to Bivariate Data Visualizations
Plotting two Categorical Variables
Introduction to Multivariate Data Visualizations
Introduction to Heatmaps and Pairplots
Quiz on Types of Charts and Visualizations
Advanced Data Visualizations
Colorscales, Facet Grids, and Sub plots
Introduction to 3D Data Visualization
Introduction to Interactive Data Visualization
Introduction to Maps using Plotly
Introduction to Funnel and Gantt Charts using Plotly
Introduction to Animated Data Visualizations using Plotly
Quiz on Advanced Data Visualizations
