Advanced Diploma in Business Analytics

Description

Course Name: Advanced Diploma in Business Analytics

Course Id: ADBA/Q1001.

Eligibility: Completion of 10+2 (higher Secondary) or equivalent.

Objective: An Advanced Diploma in Business Analytics is a highly valuable qualification for those looking to pursue or advance their careers in the data-driven world of business. The program equips students with a strong foundation in data analysis, machine learning, business intelligence, and predictive analytics, making them highly sought after in industries that rely on data for decision-making.

Duration: Six Months.

 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- 120 minutes.
• No. of Questions- 60. (Multiple Choice Questions).
• 10 Questions from each module, each carry 10 marks.
• Maximum Marks- 600, Passing Marks- 40%.
• There is no negative marking in this module.

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	41-50	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 Business Analytics: Overview of Business Analytics, Importance and Applications of Business Analytics, Types of Analytics (Descriptive, Predictive, Prescriptive), Business Intelligence vs. Business Analytics, Role of a Business Analyst, Data-Driven Decision Making, Understanding Business KPIs and Metrics, Data Collection and Sources, Business Case Studies on Analytics, Ethical Considerations in Business Analytics.

Data Handling and Preprocessing: Data Types and Structures, Handling Missing Data and Outliers, Data Cleaning and Preprocessing, Data Transformation Techniques (Scaling and Normalization), Feature Engineering and Feature Selection, Handling Categorical and Numerical Data, Exploratory Data Analysis (EDA) with Pandas and NumPy, Introduction to SQL for Business Analytics, Data Integration and Merging, Real-World Data Challenges.

Statistical Analysis for Business Decision Making: Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation), Inferential Statistics (Hypothesis Testing, Confidence Intervals), Probability Distributions (Normal, Binomial, Poisson), Correlation and Regression Analysis, Time Series Analysis for Business Forecasting, A/B Testing and Experimentation, Statistical Sampling Methods, Bayesian Analysis for Business, Monte Carlo Simulation, Business Insights from Statistical Data.

Data Visualization and Business Intelligence: Introduction to Data Visualization, Best Practices for Data Presentation, Dashboard Designing with Power BI & Tableau, Data Storytelling for Business Insights, Advanced Excel for Data Analytics, Creating Interactive Reports, Customizing Visualizations, Heatmaps and Geographic Data Visualization, Case Studies on Business Intelligence Applications, Automation of Reports and Dashboards.

Predictive Analytics and Machine Learning for Business: Introduction to Machine Learning in Business Analytics, Supervised vs. Unsupervised Learning, Regression Techniques (Linear, Logistic), Classification Algorithms (Decision Trees, Random Forest, SVM), Clustering Techniques (K-Means, Hierarchical), Time Series Forecasting (ARIMA, Exponential Smoothing), Model Evaluation Metrics (Accuracy, Precision, Recall, F1-Score), Hyperparameter Tuning and Model Optimization, Predictive Maintenance and Risk Analysis, AI-driven Business Analytics.

Big Data and Cloud Computing for Business Analytics: Introduction to Big Data Analytics, Hadoop and Spark for Business Data, NoSQL Databases (MongoDB, Cassandra), Cloud Computing for Analytics (AWS, Azure, Google Cloud), Data Warehousing and Data Lakes, Streaming Data and Real-Time Business Insights, Serverless Computing for Business, Cloud-based Machine Learning Solutions, Business Use Cases of Cloud Analytics, Security and Compliance in Cloud-Based Analytics.