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Data Analytics for Beginners
0.00 (0)
Data Analytics

Data Analytics for Beginners

Introduction to Data Analytics

64 Students Enrolled
Beginner
English
This Course Includes:
  • 42m
  • 14 Lectures
  • Full Lifetime Access
  • Access On Mobile And Tv
  • Certificate On Completion

Overview

What will students learn in your course?
  • Understand the basics of data analytics and how it applies across industries.
  • Learn the differences between data science and data analytics.
  • Explore data types, data collection methods, and storage systems.
  • Discover the four main types of data analytics (Descriptive, Diagnostic, Predictive, Prescriptive).
  • Master the data analytics framework (CRISP-DM) to execute data projects from start to finish.
  • Learn how to create impactful data visualizations and build dashboards for business intelligence.
  • Develop data storytelling skills to effectively present insights to stakeholders.
  • Gain an understanding of data privacy, security, and governance principles.
What are the requirements or prerequisites for taking your course?
  • There are no technical prerequisites for this course; it is designed for beginners. However, to maximize your learning experience, it helps to:
  • Have a curiosity for data and business problem-solving.
  • Be comfortable with basic computer skills (navigating spreadsheets, accessing online tools).
  • Be open to learning theory-based concepts, as this course focuses on understanding frameworks and methodologies rather than hands-on practice.
Who is the course for?
  • Beginners with little to no experience in data analytics.
  • Career Switchers looking to pivot into the data field.
  • Business Professionals who want to leverage data for strategic decision-making.
  • Students and Graduates eager to explore data-related career opportunities.
  • Entrepreneurs and Founders seeking data-driven insights to grow their businesses.
Description
Course Tags

Course Content

  • 8 Sections
  • 14 Lectures
  • 42m Total Length
Before Starting the Course
02m
1 Lectures

Before Starting the Course

What is Data Analytics?
0:03:42
Data Science vs Data Analytics
0:02:46
Skills & Tools for Data Analytics projects
0:04:24
Data Career Progression
0:04:45
Application of Data Analytics
0:02:19
Understanding Data
0:01:00
Data Collection, Transformation & Storage Systems
0:01:00
Types of Data Analytics
0:01:00
Data Analytics Framework
0:01:00
Data Visualization & Dashboard Development
0:10:31
Data Storytelling
0:01:00
Data Privacy & Governance
0:03:52
The End
0:02:04

About Tutor

Tobe Awo
5.00 (12)

Tobe Awo

Courses 1

With 12+ years of experience across Data Science, AI, Analytics, and Product, Tobe is a trusted leader in the Data & AI space and a former Growth Data Scientist at Google.
At Google, she led data and GenAI initiatives for the YouTube Premium Growth team, building analytics and AI-driven solutions that optimized user acquisition, experimentation, and ROI at scale.
Tobe holds a Bachelor’s and Master’s degree in Computer Science, along with postgraduate training in AI/ML from the University of Texas. Her expertise spans AI, growth analytics & data science

Today, she mentors professionals and founders using the same proven frameworks, decision models, and systems she applied at Google—to help you move from confused to confident execution.

This mentorship helps you:

✔️ Break or advance into Data Analytics, Data Science, or no-code AI roles
✔️ Build and scale AI-powered products, MVPs, or internal tools
✔️ Apply Data & AI to drive real business and career transformation
✔️ Make confident, data-backed decisions in SaaS, subscription businesses, and startups


Areas of Focus

✔️ Data Science & Growth Analytics – [Marketing & Product analytics Measurement, growth funnel analysis, User behavior analysis, Marketing Mix Modeling (MMM); Attribution models, Causal inference, Incrementality, cohort, Experimentation]
✔️ AI Product Management – [AI product design & strategy, Product roadmapping & feature prioritization; AI feasibility audit; PRDs & user stories, building an AI MVP, Translating business problems into AI solutions]
✔️ AI & Machine Learning – [Regression, Classification, Clustering, NLP; Generative AI, Agentic systems, RAG, AI Chatbot, Responsible AI, ethics & governance]

💬 Are you ready to take your career to the next level? Looking to pivot into no-code AI roles, deepen your expertise, or fast-track your career path in data & AI? Let's work together to unlock your full potential.

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