Unlocking Insights through Data: Mastering Analytics and Visualization for In-Demand Tech Proficiency
Note: Course Free for limited time and limited users(500 limit) so Enroll ASAP. If not free it means you are late. Scroll Down and click Enroll Now button to get enrolled
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Apply Coupon Code: 58A4415FE6A49D3C10B4
What you’ll learn
- Real-world 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 decision-making.
- Introduction to Python for statistical analysis, including data manipulation and visualization.
Explore related topics
This course includes:
- 17 hours on-demand video
- Assignments
- 35 downloadable resources
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
Course content
23 sections • 120 lectures • 16h 55m total length
- Excel Applications
- Understanding the Excel Interface
- Sorting and Filtering
- Conditional Formatting
- Quiz on Excel Fundamentals
- Introductions to Statistical Functions
- Introduction to Mathematical Functions
- Quiz on Statistical and Mathematical Functions
- Introduction to Lookup Functions
- Introduction to Index and Match
- Introduction to Pivot Tables
- Introduction to Pivot Charts
- Quiz on Lookup Functions, and Pivot Tables
- 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
- 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
- Scenario Manager
- Goal Seek
- Data Tables
- Solver Package
- Quiz on What If analysis
- Data Visualization Best Practices
- Types of Charts in Excel
- Creating and Formatting Charts
- Quiz on Charts and Dashboards
- Introduction to Linear Regression…
- Preliminary Forecasting Analysis….
- 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 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 Parameters and Arguments
- Introduction to Python Modules
- Introduction to Filter, Map, and Zip Functions
- Introduction to List, Set and Dictionary Comprehensions
- Introduction to Lambda Functions
- Introduction to Analytical and Aggregate Functions
- Quiz on Functions in Python
- 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
- 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
- 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
- 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
- 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 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 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
- 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
- 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
- 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
- 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
- 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
- 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 problem-solving.
Description
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.
– 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.
Who this course is for:
- Beginners with no prior programming experience.
- Students or professionals in various fields, including business, science, social sciences, and healthcare, who want to enhance their data analysis skills.
- Anyone interested in automating tasks or data analysis.
- Data analysts, researchers, and scientists seeking to strengthen their statistical foundations and Python programming skills.
- Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods.
- Professionals looking to advance their career by acquiring valuable statistical and data analysis skills.
Note: The course is free for a limited time and limited to 500 users. Enroll as soon as possible. If it is no longer free, it means you are late, and it has already exceeded its limits.
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