Web Analyst Job Preparation Complete Course

Cambridge Open Academy

Certificate of Completion (Hard Copy)

Hard copy certificate - Included

Certificate of Completion (PDF)

Digital certificate - Included

Mock Exam & Final Exam

Included in course price

In today's digital landscape, the role of a Web Analyst is pivotal in steering businesses toward success. This meticulously crafted course offers an in-depth exploration of web analytics, data interpretation, and strategic implementation. Beginning with a solid foundation in Google Analytics, you'll learn to navigate and utilize its features to monitor website performance effectively. The course delves into data analytics and statistical analysis, empowering you to transform raw data into actionable insights.

As you progress, you'll engage with advanced topics such as Big Data analytics, employing tools like PySpark, Tableau Desktop, and MongoDB to manage and analyse large datasets. The curriculum also emphasizes the importance of SQL in data science, providing you with the skills to query databases efficiently. Understanding the nuances of SEO analytics and content marketing will enable you to enhance website visibility and engagement. Additionally, the course covers essential web development skills, including HTML and CSS, ensuring you have a well-rounded skill set.

By the end of this course, you'll be equipped with the knowledge and skills to excel as a Web Analyst, capable of driving data-informed decisions and contributing significantly to your organization's digital strategy. Enroll now to embark on your journey toward becoming a proficient Web Analyst.

Course Curriculum:

» Course 01: Google Analytics for Everyone

• Section 01: Overview of Web Analytics
• Section 02: Structure of Google Analytics
• Section 03: Goal Setting
• Section 04: User Management
• Section 05: Audience Tab & Acquisition Tab
• Section 06: Conversion Tab & Dashboard Tab
• Section 07: Intelligence Tab
• Section 08: Email & Export Options

» Course 02: Data Analytics

• Module 01: Introduction to the World of Data
• Module 02: Basics of Data Analytics
• Module 03: Statistics for Data Analytics
• Module 04: Actions Taken in the Data Analysis Process
• Module 05: Gathering the Right Information
• Module 06: Storing Data
• Module 07: Data Mining
• Module 08: Excel for Data Analytics
• Module 09: Tools for Data Analytics
• Module 10: Data-Analytic Thinking
• Module 11: Data Visualisation That Clearly Describes Insights
• Module 12: Data Visualisation Tools

» Course 03: Statistical Analysis

• Module 01: The Realm of Statistics
• Module 02: Basic Statistical Terms
• Module 03: The Center of the Data
• Module 04: Data Variability
• Module 05: Binomial and Normal Distributions
• Module 06: Introduction to Probability
• Module 07: Estimates and Intervals
• Module 08: Hypothesis Testing
• Module 09: Regression Analysis
• Module 10: Algorithms, Analytics and Predictions
• Module 11: Learning From Experience: The Bayesian Way
• Module 12: Doing Statistics: The Wrong Way
• Module 13: How We Can Do Statistics Better

» Course 04: Big Data Analytics with PySpark Tableau Desktop and MongoDB

• Section 01: Introduction
• Section 02: Setup And Installations
• Section 03: Data Processing With PySpark And MongoDB
• Section 04: Machine Learning With PySpark And MLlib
• Section 05: Creating The Data Pipeline Scripts
• Section 06: Tableau Data Visualization

» Course 05: SQL for Data Science, Data Analytics and Data Visualization

• Section 01: Getting Started
• Section 02: SQL Server setting up
• Section 03: SQL Azure Data Studio
• Section 04: SQL Database basic SSMS
• Section 05: SQL Statements for DATA
• Section 06: SQL Data Structure statements
• Section 07: SQL User Management
• Section 08: SQL Statement Basic
• Section 09: Filtering Data rows
• Section 10: Aggregate functions
• Section 11: SQL Query statements
• Section 12: SQL Group by statement
• Section 13: JOINS for Multiple table Data Analysis
• Section 14: SQL Constraints
• Section 15: Views
• Section 16: Advanced SQL commands
• Section 17: SQL Stored procedures
• Section 18: Azure Data Studio Visualization
• Section 19: Azure Studio SQL for Data Analysis
• Section 20: Import & Export data
• Section 21: Backup and Restore Database

and more with other courses.

Our Specialised Delivery Method:

• Learn by Doing: Interactive activities keep you engaged.
• Go Mobile: Works on any device, no downloads needed.
• Easy to Use: Simple design for all learners.
• Track Progress: Stay motivated with clear progress tracking.
• Visually Appealing: Enjoyable learning experience.

Join us today to unlock the potential of your Web Analyst skills and elevate your career to new heights.

• Aspiring Web Analysts seeking comprehensive preparation.
• Digital marketing professionals aiming to enhance their analytical skills.
• Data enthusiasts interested in web analytics and data interpretation.
• Individuals looking to transition into the field of web analysis.

• No prior knowledge needed
• Compatible with any internet-enabled device, including computers, tablets, and smartphones.
• Consistent learning experience
• Accessible anywhere, anytime
• No limitations on access
• Use Wi-Fi or mobile data

After finishing the course, you can advance your profession. Look into jobs like:

• Junior Web Analyst: £25,000 – £35,000
• Digital Data Analyst: £28,000 – £40,000
• Web Performance Analyst: £30,000 – £45,000
• SEO/Analytics Specialist: £32,000 – £48,000
• Web Analytics Manager: £40,000 – £60,000
• Head of Digital Analytics: £50,000 – £75,000

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