Description
Course Name: Certificate in Data Analysis
Course Id: CDE/Q1001.
Eligibility: 10+2 Grade (higher secondary) or Equivalent.
Duration: Two Month.
Objective: This course is designed to provide learners with a strong foundation in data collection, cleaning, processing, and interpretation techniques. It covers statistical methods, data visualization, and the use of analytical tools to extract meaningful insights from datasets.
How to Enroll and Get Certified in Your Chosen Course:
Step 1: Choose the course you wish to get certified in.
Step 2: Click on the “Enroll Now” button.
Step 3: Proceed with the enrollment process.
Step 4: Enter your billing details and continue to course fee payment.
Step 5: You will be redirected to the payment gateway. Pay the course and exam fee using one of the following methods:
Debit/Credit Card, Wallet, Paytm, Net Banking, UPI, or Google Pay.
Step 6: After successful payment, you will receive your study material login ID and password via email within 48 hours of fee payment.
Step 7: Once you complete the course, take the online examination.
Step 8: Upon passing the examination, you will receive:
• A soft copy (scanned) of your certificate via email within 7 days of examination.
• A hard copy (original with official seal and signature) sent to your address within 45 day of declaration of result.
Step 9: After certification, you will be offered job opportunities aligned with your area of interest.
Online Examination Detail:
Duration- 60 minutes.
No. of Questions- 30. (Multiple Choice Questions).
Maximum Marks- 100, Passing Marks- 40%.
There is no negative marking in this module.
| Marking System: | ||||||
| S.No. | No. of Questions | Marks Each Question | Total Marks | |||
| 1 | 10 | 5 | 50 | |||
| 2 | 5 | 4 | 20 | |||
| 3 | 5 | 3 | 15 | |||
| 4 | 5 | 2 | 10 | |||
| 5 | 5 | 1 | 5 | |||
| 30 | 100 | |||||
| How Students will be Graded: | ||||||
| S.No. | Marks | Grade | ||||
| 1 | 91-100 | O (Outstanding) | ||||
| 2 | 81-90 | A+ (Excellent) | ||||
| 3 | 71-80 | A (Very Good) | ||||
| 4 | 61-70 | B (Good) | ||||
| 5 | 51-60 | C (Average) | ||||
| 6 | 40-50 | P (Pass) | ||||
| 7 | 0-40 | F (Fail) | ||||
Key Benefits of Certification- Earning a professional certification not only validates your skills but also enhances your employability. Here are the major benefits you gain:
Practical, Job-Ready Skills – Our certifications are designed to equip you with real-world, hands-on skills that match current industry demands — helping you become employment-ready from day one.
Lifetime Validity – Your certification is valid for a lifetime — no renewals or expirations. It serves as a permanent proof of your skills and training.
Lifetime Certificate Verification – Employers and institutions can verify your certification anytime through a secure and reliable verification system — adding credibility to your qualifications.
Industry-Aligned Certification –All certifications are developed in consultation with industry experts to ensure that what you learn is current, relevant, and aligned with market needs.
Preferred by Employers – Candidates from ISO-certified institutes are often prioritized by recruiters due to their exposure to standardized, high-quality training.
Free Job Assistance Based on Your Career Interests – Receive personalized job assistance and career guidance in your preferred domain, helping you land the right role faster.
Syllabus:-
Introduction to Data Analysis: Definition and Importance of Data Analysis, Types of Data (Structured and Unstructured), Data Analysis Process and Workflow, Key Skills for a Data Analyst, Common Data Analysis Tools and Software, Applications of Data Analysis in Various Industries, Ethical Considerations in Data Handling, Career Opportunities in Data Analysis.
Data Collection and Cleaning: Sources of Data (Primary and Secondary), Data Collection Methods (Surveys, Web Scraping, APIs), Data Cleaning Techniques, Handling Missing and Duplicate Data, Data Transformation and Standardization, Data Quality Assessment, Introduction to Data Wrangling, Best Practices for Data Preparation.
Exploratory Data Analysis (EDA): Understanding Data Distribution, Descriptive Statistics (Mean, Median, Mode), Measures of Variability (Standard Deviation, Variance, Range), Detecting Outliers and Anomalies, Correlation and Causation, Data Sampling Techniques, Introduction to Data Profiling, Using Python or Excel for EDA.
Data Visualization: Principles of Effective Data Visualization, Types of Charts and Graphs, Using Excel for Basic Visualization, Introduction to Power BI/Tableau, Creating Dashboards for Data Representation, Interactive Visualizations, Data Storytelling Techniques, Common Visualization Mistakes to Avoid.
Statistical Data Analysis: Introduction to Probability and Statistics, Hypothesis Testing and Confidence Intervals, Regression Analysis (Linear and Logistic), ANOVA and Chi-Square Test, Time Series Analysis, Bayesian Statistics Basics, Statistical Inference for Decision Making, Common Statistical Errors.
Data Analytics Using Excel & SQL: Data Manipulation in Excel (Pivot Tables, Formulas, Macros), Introduction to SQL for Data Extraction, Writing SQL Queries (SELECT, JOIN, GROUP BY), Data Filtering and Sorting, Aggregate Functions in SQL, Connecting SQL with Visualization Tools, Importing and Exporting Data, Hands-on SQL Exercises.
Job Opportunities after Certificate in Data Analysis
Graduates of this program gain skills in data collection, cleaning, visualization, statistical analysis, and use of tools like Microsoft Excel, SQL, Python, Power BI, and Tableau, preparing them for roles in analytics and business intelligence.
Key Career Options: Data Analyst, Business Analyst (Entry Level), MIS Executive, Reporting Analyst, Data Visualization Analyst, Operations Analyst, Junior Data Scientist, Market Research Analyst, Financial Data Analyst, Dashboard Developer.
Salary Range (India):
Entry-level: ₹3–6 LPA
Mid-level: ₹6–12 LPA
Senior-level: ₹12–30+ LPA (higher with advanced analytics & AI skills)
Industries Hiring Graduates: IT & Software Companies, Banking & Financial Services, E-commerce Companies, Healthcare Analytics, Consulting Firms, Marketing Agencies, EdTech Companies, Manufacturing & Supply Chain, Government & Public Sector.
Skills Developed: Data cleaning, data visualization, statistical analysis, Excel & dashboarding, SQL queries, basic programming, problem-solving, and business insights generation.
Graduates can progress to roles like Senior Data Analyst, Data Scientist, Business Intelligence Manager, or specialize further in AI, machine learning, or big data analytics with advanced certifications and project experience.
