This comprehensive training program is designed to equip students with the skills required to secure entry-level data and marketing analyst roles with target salaries of $55,000 or more. The curriculum includes advanced Excel, SQL, Python, Google Analytics, and marketing analytics. Additionally, it incorporates career advancement workshops, mock interviews, and portfolio development.
Target Audience:
- No prior paid experience in Data Analytics
- Fluent in English
- Interested in full-time employment as a Data or Marketing Analyst
Program Structure:
- Duration: 20 weeks
- Delivery Mode: 100% Remote
- Schedule: 4 days per week, 2 hours per session
- Assessments: Weekly projects, quizzes, and final capstone project
Narayan N
Author
Do you need a Digital Marketing Specialist? or, Do you need me to manage your PHP projects? Hi, I am Narayan a full stak developer & Digital Marketing Specialist from Queens, NY. With over a decade of experience managing web technologies, digital marketing campaigns, and eCommerce operations. I’m known for delivering high-quality, customized solutions that meet your business needs, improving performance, and driving sales growth.
Week 1-2: Orientation and Data Analysis Foundations
Program Orientation and Goal Setting
Lesson 1 of 5 within section Week 1-2: Orientation and Data Analysis Foundations.
You must enroll in this course to access course content.
Overview of Data Analytics and Marketing Analytics
Lesson 2 of 5 within section Week 1-2: Orientation and Data Analysis Foundations.
You must enroll in this course to access course content.
Data Types, Data Sources, and Data Collection
Lesson 3 of 5 within section Week 1-2: Orientation and Data Analysis Foundations.
You must enroll in this course to access course content.
Introduction to Excel: Data Entry, Formatting, Basic Formulas
Lesson 4 of 5 within section Week 1-2: Orientation and Data Analysis Foundations.
You must enroll in this course to access course content.
Project: Create a Marketing Dashboard using Excel
Lesson 5 of 5 within section Week 1-2: Orientation and Data Analysis Foundations.
You must enroll in this course to access course content.
Week 3-4: Advanced Excel for Data Analysis
Pivot Tables and Pivot Charts
Lesson 1 of 5 within section Week 3-4: Advanced Excel for Data Analysis.
You must enroll in this course to access course content.
Data Visualization Techniques
Lesson 2 of 5 within section Week 3-4: Advanced Excel for Data Analysis.
You must enroll in this course to access course content.
Advanced Formulas and Functions
Lesson 3 of 5 within section Week 3-4: Advanced Excel for Data Analysis.
You must enroll in this course to access course content.
Data Cleaning and Preparation
Lesson 4 of 5 within section Week 3-4: Advanced Excel for Data Analysis.
You must enroll in this course to access course content.
Project: Marketing Campaign Analysis using Advanced Excel
Lesson 5 of 5 within section Week 3-4: Advanced Excel for Data Analysis.
You must enroll in this course to access course content.
Week 5-6: Introduction to SQL for Data Analysis
Database Basics: Relational Databases and ER Diagrams
Lesson 1 of 5 within section Week 5-6: Introduction to SQL for Data Analysis.
You must enroll in this course to access course content.
SQL Syntax: SELECT, WHERE, ORDER BY, JOIN
Lesson 2 of 5 within section Week 5-6: Introduction to SQL for Data Analysis.
You must enroll in this course to access course content.
Data Filtering and Aggregation
Lesson 3 of 5 within section Week 5-6: Introduction to SQL for Data Analysis.
You must enroll in this course to access course content.
Data Export and Reporting
Lesson 4 of 5 within section Week 5-6: Introduction to SQL for Data Analysis.
You must enroll in this course to access course content.
Project: SQL Query for Customer Insights Analysis
Lesson 5 of 5 within section Week 5-6: Introduction to SQL for Data Analysis.
You must enroll in this course to access course content.
Week 7-8: Advanced SQL Techniques
Advanced Queries: Subqueries, Nested Queries, CTEs
Lesson 1 of 4 within section Week 7-8: Advanced SQL Techniques.
You must enroll in this course to access course content.
Data Manipulation: INSERT, UPDATE, DELETE
Lesson 2 of 4 within section Week 7-8: Advanced SQL Techniques.
You must enroll in this course to access course content.
Data Analysis with SQL: Calculated Fields, Case Statements
Lesson 3 of 4 within section Week 7-8: Advanced SQL Techniques.
You must enroll in this course to access course content.
Project: Sales Data Analysis using Advanced SQL
Lesson 4 of 4 within section Week 7-8: Advanced SQL Techniques.
You must enroll in this course to access course content.
Week 9-10: Python for Data Analysis – Introduction
Python Environment Setup (Jupyter Notebook, Anaconda)
Lesson 1 of 5 within section Week 9-10: Python for Data Analysis – Introduction.
You must enroll in this course to access course content.
Data Structures: Lists, Tuples, Dictionaries
Lesson 2 of 5 within section Week 9-10: Python for Data Analysis – Introduction.
You must enroll in this course to access course content.
Data Analysis Libraries: Pandas, NumPy
Lesson 3 of 5 within section Week 9-10: Python for Data Analysis – Introduction.
You must enroll in this course to access course content.
Data Cleaning and Preparation in Python
Lesson 4 of 5 within section Week 9-10: Python for Data Analysis – Introduction.
You must enroll in this course to access course content.
Project: Data Cleaning for a Marketing Dataset
Lesson 5 of 5 within section Week 9-10: Python for Data Analysis – Introduction.
You must enroll in this course to access course content.
Week 11-12: Python for Data Analysis – Advanced
Data Visualization with Matplotlib and Seaborn
Lesson 1 of 5 within section Week 11-12: Python for Data Analysis – Advanced.
You must enroll in this course to access course content.
Exploratory Data Analysis (EDA)
Lesson 2 of 5 within section Week 11-12: Python for Data Analysis – Advanced.
You must enroll in this course to access course content.
Data Analysis with Pandas
Lesson 3 of 5 within section Week 11-12: Python for Data Analysis – Advanced.
You must enroll in this course to access course content.
Lesson 4 of 5 within section Week 11-12: Python for Data Analysis – Advanced.
You must enroll in this course to access course content.
Project: Exploratory Data Analysis for Social Media Data
Lesson 5 of 5 within section Week 11-12: Python for Data Analysis – Advanced.
You must enroll in this course to access course content.
Week 13-14: Google Analytics and Marketing Analytics
Introduction to Google Analytics
Lesson 1 of 5 within section Week 13-14: Google Analytics and Marketing Analytics.
You must enroll in this course to access course content.
Setting Up and Navigating GA Dashboard
Lesson 2 of 5 within section Week 13-14: Google Analytics and Marketing Analytics.
You must enroll in this course to access course content.
Analyzing User Behavior and Conversion Tracking
Lesson 3 of 5 within section Week 13-14: Google Analytics and Marketing Analytics.
You must enroll in this course to access course content.
Key Metrics: Sessions, Bounce Rate, CTR, ROI
Lesson 4 of 5 within section Week 13-14: Google Analytics and Marketing Analytics.
You must enroll in this course to access course content.
Project: Google Analytics Marketing Campaign Report
Lesson 5 of 5 within section Week 13-14: Google Analytics and Marketing Analytics.
You must enroll in this course to access course content.
Week 15-16: Data-Driven Marketing Strategies
Marketing KPIs and Metrics
Lesson 1 of 4 within section Week 15-16: Data-Driven Marketing Strategies.
You must enroll in this course to access course content.
A/B Testing and Marketing Experiments
Lesson 2 of 4 within section Week 15-16: Data-Driven Marketing Strategies.
You must enroll in this course to access course content.
Predictive Analytics for Marketing
Lesson 3 of 4 within section Week 15-16: Data-Driven Marketing Strategies.
You must enroll in this course to access course content.
Project: Marketing Performance Analysis using Python and Excel
Lesson 4 of 4 within section Week 15-16: Data-Driven Marketing Strategies.
You must enroll in this course to access course content.
Week 17-18: Capstone Project Development
Project Selection and Scope Definition
Lesson 1 of 5 within section Week 17-18: Capstone Project Development.
You must enroll in this course to access course content.
Data Collection and Cleaning
Lesson 2 of 5 within section Week 17-18: Capstone Project Development.
You must enroll in this course to access course content.
Data Analysis and Reporting
Lesson 3 of 5 within section Week 17-18: Capstone Project Development.
You must enroll in this course to access course content.
Visualization and Insights Presentation
Lesson 4 of 5 within section Week 17-18: Capstone Project Development.
You must enroll in this course to access course content.
Lesson 5 of 5 within section Week 17-18: Capstone Project Development.
You must enroll in this course to access course content.
Week 19: Capstone Project Presentation
Present Project Findings to a Panel of Industry Mentors
Lesson 1 of 3 within section Week 19: Capstone Project Presentation.
You must enroll in this course to access course content.
Receive Feedback and Recommendations
Lesson 2 of 3 within section Week 19: Capstone Project Presentation.
You must enroll in this course to access course content.
Lesson 3 of 3 within section Week 19: Capstone Project Presentation.
You must enroll in this course to access course content.
Week 20: Career Advancement and Job Readiness
Resume Building and Portfolio Development
Lesson 1 of 4 within section Week 20: Career Advancement and Job Readiness.
You must enroll in this course to access course content.
Lesson 2 of 4 within section Week 20: Career Advancement and Job Readiness.
You must enroll in this course to access course content.
Mock Interviews and Interview Techniques
Lesson 3 of 4 within section Week 20: Career Advancement and Job Readiness.
You must enroll in this course to access course content.
Job Search Strategies and Networking
Lesson 4 of 4 within section Week 20: Career Advancement and Job Readiness.
You must enroll in this course to access course content.
