Certificate in Management (Business Analytics)

Description

Course Name: Certificate in Management (Business Analytics)

Course Id: CIMBAQ1001.

Eligibility: Graduate or Equivalent.

Objective: The Certificate in Management (Business Analytics) is a specialized short-term program aimed at equipping individuals with the skills and knowledge required to analyze business data and support decision-making processes. This program combines management principles with analytical tools and techniques, preparing learners for roles in data-driven industries.

Duration: 90 Hrs (Equivalent to 3 Months).

How You will Get Diploma Certificate:

Step 1- Select your Course for Certification.

Step 2- Click on Enroll Now.

Step 3- Proceed to Enroll Now.

Step 4- Fill Your Billing Details and Proceed to Pay.

Step 5- You Will be Redirected to Payment Gateway, Pay Course and Exam Fee by Following Options.

Card(Debit/Credit), Wallet, Paytm, Net banking, UPI and Google pay.

Step 6- After Payment You will get Study Material Login id and Password on your email id.

Step 7- After Completion of  Course Study give Online Examination.

Step 8- After Online Examination you will get Diploma Certificate soft copy(Scan Copy) and Hard Copy(Original With Seal and Sign).

Step 9- After Certification you will receive Prospect Job Opportunities as per your Interest Area.

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)

Benefits of Certification:

• Government Authorized Assessment Agency Certification.
• Certificate Valid for Lifetime.
• Lifetime Verification of Certificate.
• Free Job Assistance as per your Interest Area.

Syllabus:

Introduction to Business Analytics: Definition and scope of business analytics, Importance of analytics in decision making, Types of business analytics (descriptive, predictive, prescriptive), Business intelligence vs business analytics, Data-driven decision-making process, Role of big data in analytics, Key components of business analytics systems, Overview of business analytics tools and software, Business analytics in different industries, Case studies on the application of business analytics.

Data Collection and Management: Sources of business data (internal and external), Types of data: structured and unstructured, Data collection techniques and methods, Data cleaning and preprocessing, Data storage and retrieval systems, Data quality management, Data integration from various sources, Introduction to data warehousing, Data governance and security, Case studies on data management in business analytics.

Statistical Methods for Business Analytics: Basic statistical concepts for business analytics, Descriptive statistics: mean, median, mode, Variability and spread: range, variance, standard deviation, Probability distributions in analytics, Inferential statistics: hypothesis testing, Regression analysis and correlation, Time series analysis for business forecasting, Statistical tools and software for analysis, Case studies on applying statistics in business problems.

Predictive Analytics and Modeling: Introduction to predictive analytics, Techniques in predictive modeling (linear and logistic regression), Data mining and machine learning in business analytics, Model building and validation, Overfitting and underfitting in models, Cross-validation and performance metrics, Predictive analytics tools and software, Application of predictive analytics in business decision-making, Introduction to artificial intelligence in analytics, Case studies on predictive analytics in various industries

Data Visualization and Reporting: Importance of data visualization in business analytics, Principles of effective data visualization, Types of data visualization (charts, graphs, heat maps), Tools for data visualization (Tableau, Power BI, etc.), Creating interactive dashboards, Key performance indicators (KPIs) and metrics, Reporting business insights through visual representation, Storytelling with data, Communicating complex data effectively, Case studies on successful data visualization strategies.

Prescriptive Analytics and Optimization: Introduction to prescriptive analytics, Optimization techniques in business analytics, Linear programming and its applications, Decision analysis and making under uncertainty, Simulation modeling and Monte Carlo methods, Resource allocation and capacity planning, Cost-benefit analysis in decision-making, Application of prescriptive analytics in supply chain and operations, Use of prescriptive analytics in marketing and finance, Case studies on prescriptive analytics in business optimization.