IACAIP courses
Data Analytics
Course Information
Price:
Free
250
Instructors:
4 Instructors
Lessons:
45 lessons
Duration:
112 hours
Level:
Advanced
Quizzes:
180 Quizes
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Data Analytics Professional Program
Course Description
This course will teach you how to use large data sets to make critical decisions. Designed for analysts, digital marketers, sales managers, product managers, and data novices alike, this program introduces the essentials of data analysis while providing hands-on experience with industry-standard tools. You’ll work with Excel, SQL, Power BI, and Python to collect, clean, analyze, and visualize real-world, large-scale datasets, and create dashboards to communicate actionable insights effectively.
Throughout the program, you will complete practical exercises, coding challenges, and projects that culminate in a portfolio-grade final project, allowing you to showcase your analytical skills to classmates, instructors, and potential employers.
What You Will Learn
By the end of this course, you will be able to:
Collect, clean, and analyze large datasets using Excel, SQL, Power BI, and Python.
Present data-driven insights to key stakeholders through dashboards, charts, and other visualizations.
Tell compelling stories with data, translating complex findings into understandable, actionable recommendations.
Develop problem-solving skills by completing coding challenges and project-based exercises.
Build a professional portfolio that demonstrates your analytical capabilities and readiness for real-world data projects.
Skill Assessment & Requirements
To successfully complete this program, participants are expected to:
Attend all class sessions and participate actively.
Complete all homework assignments to reinforce learning.
Complete and present the final capstone project to demonstrate applied analytical skills.
Upon passing the course requirements, learners will receive a certificate of completion, validating their data analytics expertise.
Prerequisites
If you are new to Excel, our Admissions team may recommend a short pre-course Excel refresher.
Learners with basic Excel and Power BI skills will benefit from the curriculum by building advanced analytical capabilities.
Technical Requirements:
A laptop (PC or Mac) no older than four years capable of running the latest operating system.
For remote learning: a webcam, headphones, and reliable internet access.
Capstone Project
The course culminates in a final data analytics project, allowing you to address a real-world problem in your field of interest.
Project Workflow Includes:
Data Acquisition & Cleaning: Identify and prepare relevant datasets for analysis.
Analysis: Apply Excel, SQL, Power BI, and Python to extract insights.
Visualization: Build clear, interactive dashboards and charts to communicate findings.
Insights & Recommendations: Present actionable conclusions to stakeholders.
Students present their projects to instructors and peers, demonstrating:
The full workflow from data collection to analysis.
Clear visualizations and dashboards.
High-level insights with practical implications.
Instructors guide participants to validate the scope of the project and ensure feasibility.
Pre-Work: Recommended Self-Paced Learning
To help you start strong, we recommend self-paced preparation in the following areas:
Python Programming
Python is widely used in data science for its versatility and ease of use. In this course, you will learn:
Core Python Concepts: Data types, variables, conditionals, loops, and error handling.
Data Structures: Lists, sets, dictionaries, and tuples to store and organize complex data.
Functions & Object-Oriented Programming: Create reusable, modular code.
Data Analysis & Visualization: Apply Python skills to analyze datasets and create charts to reveal insights.
By mastering Python, you will gain a powerful toolset for analyzing, manipulating, and visualizing large datasets.
Data Analysis in Excel
Excel remains one of the most important tools for analysts. This course will teach you:
Time-saving techniques: Keyboard shortcuts, conditional formatting, and dynamic formulas.
Data cleaning & transformation: Convert and clean text, date, and numerical data.
Advanced functions: Over 35 functions including CONCATENATE, VLOOKUP, and AVERAGEIF(S).
Hands-on practice: Analyze real-world Kickstarter data to identify trends, patterns, and predictors of success.
By the end of the Excel module, you will be able to analyze complex datasets efficiently and draw actionable insights.
Why This Course is Valuable
This program is perfect for anyone looking to launch or advance their career in data analytics. Whether your goal is to make data-driven decisions in marketing, sales, or product management, or to develop analytical problem-solving skills from scratch, this course provides the tools, techniques, and real-world experience to succeed.
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