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Mastering Data Analytics with Excel and Python

Unlocking Insights through Data: Mastering Analytics and Visualization for In-Demand Tech Proficiency.

Course Includes

  • course Recorded Lessons: 142
  • course Recorded Hours: 15
  • course Duration: 15 days (Avg)

Course Features

  • course Access on mobile
  • course TDP Assessment Test
  • course 3 Jobs Available
Top Skills Covered
Overview
Course Description

Embarking on a transformative journey into the dynamic realm of Data Analytics and Visualization promises to equip participants with essential and sought-after 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 hands-on 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 industry-standard tools like Matplotlib and Seaborn to create compelling and informative data visualizations.

Upon completion of the course, participants will possess a well-rounded skill set in data analytics and visualization. They will be equipped to tackle real-world challenges and contribute meaningfully to data-driven decision-making in any professional setting.

Joining this transformative journey promises to elevate participants into proficient and sought-after tech professionals in the field of data analytics and visualization. With these skills, participants will be well-positioned to excel in the ever-evolving landscape of data science and analytics.

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.

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 problem-solving.
Course Content
120 Lessons | 3 Quiz | 15:00 Total hours
Excel Fundamentals
Statistical and Mathematical Functions in Excel
Lookup functions, and Pivot Tables
Logical Functions, and Text Functions
Data Cleaning, and Feature engineering
What If analysis
Charts and Dashboards
Linear Regression and Forecasting
Basics of Python
Introduction to Data Structures
Introduction to Functions in Python
Strings and Regular Expressions
Loops and Conditionals
OOPs and Date-Time
Introduction to Statistics
Introduction to Descriptive Statistics
Introduction to Basic and Conditional Probability
Introduction to Inferential Statistics
Introduction to Hypothesis Testing
Introduction to Numpy and Pandas
Advanced Functions in Pandas
Types of Charts and Visualizations
Advanced Data Visualizations
About the instructor
4.5 Instructor Rating
course

4 Courses

course

2+ Lesson

course

4 Students enrolled