Data Analyst

Data Analyst Course

Are you ready to launch a rewarding career as a Data Analyst? Our company offers a comprehensive 4-month Data Analyst course that equips you with the skills and knowledge to excel in this high-demand field. With a focus on hands-on training and practical applications, our program covers all essential topics, from data manipulation and visualization to statistical analysis and business intelligence tools. Our expert instructors bring real-world experience to every lesson, ensuring you gain insights that are directly applicable to today’s job market. Plus, our course includes certification in leading platforms like Power BI and SQL, giving you the credentials needed to stand out as a qualified Data Analyst. Join us and take the first step toward a data-driven career!

Why choose EdTech Informative?

Choosing EdTech Informative means investing in a brighter future with guaranteed success in data analytics and data science. Recognized as the USA’s best EdTech platform, we offer comprehensive courses designed to equip you with in-demand skills, guided by industry experts who bring real-world insights into every session. We focus on hands-on learning through real-world projects, ensuring you build a strong portfolio that stands out to employers. Our commitment to your success sets us apart—we provide 100% job placement support to help you secure your dream job. At EdTech Informative, we don’t just teach; we transform careers. Join us today and take the first step toward a rewarding future!

Why Join This Program?

Microsoft Advantage
Gain access to professional-level training directly from Microsoft, showcase your technical expertise, and earn a highly valued, employer-recognized Azure certification from Microsoft.

Generative AI Edge
Attend live sessions on cutting-edge AI trends, including generative AI tools, prompt engineering, and more to keep you at the forefront of technology.

Hands-on Learning
Our data science course, taught live by industry experts, emphasizes practical, applied learning. Engaging capstone projects ensure you acquire the skills needed to excel in the job market.

Placement Support
Receive 100% placement assistance through our dedicated recruitment agency. With a network of over 250 hiring partners, we achieve an impressive placement success rate of 80%.

Data Analyst Certification Course Learning Path

A well-structured learning path for a Data Analyst Certification Course can help students progress effectively from foundational knowledge to advanced data analysis skills. Here’s a recommended learning path for a comprehensive Data Analyst Certification course:

1. Introduction to Data Analytics

• Overview of the Data Analytics industry
• Role and responsibilities of a Data Analyst
• Introduction to popular data tools and platforms

2. Data Fundamentals

• Data types and data structures
• Data collection and data management
• Introduction to databases and SQL

3. Excel for Data Analysis

• Basics of Excel: Functions, formulas, and data handling
• Advanced Excel: Pivot tables, charts, and conditional formatting
• Data cleaning and preparation in Excel

4. SQL and Relational Databases

• SQL fundamentals: Basic queries, joins, and aggregations
• Data extraction, transformation, and loading (ETL) processes
• Advanced SQL: Nested queries, views, and stored procedures

5. Data Visualization and Reporting

• Introduction to data visualization principles
• Tools for data visualization: Tableau, Power BI, or similar
• Creating dashboards and reports
• Effective storytelling with data

6. Statistics and Probability for Data Analysis

• Basics of statistics: Mean, median, mode, and standard deviation
• Probability concepts: Distribution, correlation, and regression
• Hypothesis testing and statistical inference

7. Python for Data Analysis

• Python basics: Variables, data types, and control structures
• Data analysis libraries: Pandas, NumPy, and Matplotlib
• Data cleaning, manipulation, and visualization in Python

8. Data Cleaning and Preprocessing

• Techniques for handling missing and inconsistent data
• Data normalization, standardization, and transformation
• Data quality checks and best practices

9. Machine Learning Fundamentals

• Introduction to machine learning for data analysts
• Basic algorithms: Linear regression, classification, and clustering
• Evaluation metrics and model interpretation

10. Real-World Projects and Case Studies

• End-to-end project experience with real-world data sets
• Developing a comprehensive data analysis report
• Industry-specific case studies to build domain knowledge

11. Capstone Project and Certification Preparation

• Capstone project: Solving a business problem with data analysis
• Mock exams and certification preparation
• Resume building and interview preparation for data analyst roles

This learning path builds strong foundational skills and progresses toward advanced data analysis concepts. By the end of the course, students should be able to handle data analysis projects independently and apply for data analyst roles confidently.