

Amity Online Certificate in Time Series Forecasting





Amity Online Certificate in Time Series Forecasting - Course Details
Developed in collaboration with KPMG India, the Amity Online Certificate in Time Series Forecasting comes with UGC Entitlement and WES Accreditation. It is a 16-hour, 5-module certification course that uses Excel and Python (Pandas, Statsmodels) as the main technologies and is meant for learners without any background in statistics or forecasting.
The syllabus includes the basics of time series analysis, forecasting using the Moving Average techniques, Naïve Bayes & variants, Exponential Smoothing & Simulation using Excel, and ARIMA models.
This online certificate degree makes it possible for graduates to seek employment as a Forecasting Analyst, Data Analyst, and Business Intelligence Analyst in sectors such as retail, financial services, and supply chain management.
Learners become entitled to a paid or unpaid internship, depending on organizational norms and on a first-come, first-served basis.
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Amity Online Certificate in Time Series Forecasting Fees 2026
The time series forecasting online certificate fees are offered at a special launch price, making it accessible for learners looking to build time series and forecasting skills without a significant financial commitment.
₹13,000/-
Total Program Fee
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Amity Online Certificate in Time Series Forecasting Syllabus
The Time Series Forecasting certification curriculum covers 5 structured modules, developed in collaboration with KPMG India.
Understanding what makes data a time series data
Examples of time series data
Components of time series data - Trends, Seasons, Cycles
Decomposition of time series data
Quick Facts
- Industry Collaboration: Learn from KPMG professionals and consultants.
- Internship Opportunity: Eligible to apply for paid/unpaid internships after successful completion.
Amity Online Scholarships: Up to 45% Off First Semester Fees


Divyaang (for learners with special needs)
Applicants are required to submit a valid certificate of disability issued by a recognized authority in accordance with government norms.
Defence Personnel Scholarship
Applicants are required to have a minimum of 2 years of service in the defence forces with a valid Identity Card number.
Amity Alumni Scholarship
Applicants must have completed their previous degree from Amity University and are applying for further studies within the institution.
Merit-Based Scholarship
Applicants must have academic excellence with a minimum 85% aggregate in the previous qualification.
Sports Scholarship (CHAMPS)
Applicants must be a state, national, or international-level sportsperson with a valid affiliation from the respective sports federation.
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Key Insights You must know before choosing
Amity Online Certificate in Time Series Forecasting in 2026
Your Amity Online Certificate in Time Series Forecasting Sample
- You will receive a globally recognized Time Series Forecasting certificate from Amity Online upon successful completion.
- This certificate reflects practical, industry-relevant training in your chosen domain, adding credibility to your professional profile.

Exam Pattern
Amity Online Certificate in Time Series Forecasting Eligibility Criteria
Educational Qualification
Candidates who have completed higher secondary education, graduation, or post-graduation from a recognized institution can apply.
Suitable For
Students, analysts, data professionals, finance and supply chain practitioners, and working professionals looking to build forecasting capabilities regardless of their academic background.
Prior Experience
No prior experience in statistics, Python, or time series analysis is required. The program is designed for beginners.
Amity Online Certificate in Time Series Forecasting Admission Process 2026
Amity Online Certificate in Time Series Forecasting Placement 2026: Jobs, Salaries & Hiring Partners
Placement Highlights
Note: Salary figures are indicative, based on industry averages. Actual packages may vary depending on experience, role, and employer.














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Clear Your Doubts Before Enrolling
in Amity Online Certificate in Time Series Forecasting
The course covers Moving Average Techniques, Naïve Bayes and its variants, Exponential Smoothing, Simulation using Excel, and ARIMA (Auto-Regressive Integrated Moving Average Model).
The software tools used in this certification for time series analysis are Microsoft Excel for Exponential Smoothing and Simulation. In addition, Python with Pandas and Statsmodels modules is also used for time series analysis and ARIMA modeling.
The online certificate in time series forecasting is in collaboration with KPMG India. This makes the certification industry-oriented and gives learners industry insights related to time series forecasting and analytics.
Yes. The course is designed for beginners and requires no prior knowledge in statistics, Python programming, or forecasting methods. Everything is taught step by step, from basics about what makes data a time series to building ARIMA models in the last module.
While other data analytics programs cover general subjects such as data cleansing and visualization, this program will concentrate on time-based data, deconstructing trends and seasonality, creating moving average and ARIMA models, as well as forecasting future values based on past data.
The skills in time series forecasting are widely utilized in the retail sector (forecasting demand), financial industry (forecasting stocks and revenues), supply chain management (inventory planning), healthcare (forecasting patient volumes), and energy sector (consumption planning).
Learners can choose among job positions such as Forecasting Analyst, Demand Planning Analyst, Data Analyst, Business Intelligence Analyst, Financial Analyst (Forecasting), Supply Chain Analyst, and entry-level Analytics Consultant within the IT, BFSI, retail, healthcare, and logistics sectors.
Yes. Upon successful completion of this program, learners will become eligible to apply for internships, paid or unpaid. The seats for the internships are limited and allocated on a first-come, first-served basis, depending upon the norms of partnering organizations.
This certification pairs well with courses in Descriptive Analytics, Predictive Analytics using Python, and Business Analytics Professional. Together, they form a progression from data pre-processing and exploration to statistical modelling and domain application, giving learners a broader analytics profile.
The certification builds applied forecasting knowledge and a credible credential from a UGC-entitled institution. Career outcomes depend on individual experience, portfolio, and job market conditions. Amity Online's career services are available separately to support job search and profile development.
Students must have passed the higher secondary level of education (10+2) or any higher educational qualification from a recognized institute. Students from any stream, such as commerce, science, arts, and engineering, are all eligible to apply.
The enrollment procedure consists of three stages, including filling out the online application form, making payment of course fees worth ₹13,000, and getting confirmation from the admission department regarding enrollment. Platform access is provided shortly after confirmation, and learners can begin at any time.
The batch intake for 2026 is currently open with a limited number of internship spots available. Learners are advised to enroll early to secure internship eligibility. Subject availability may vary after the initial batch closes.
The program is delivered through recorded sessions with no fixed class schedules, giving learners the ability to progress through all 5 modules at a pace that suits their schedule. Specific completion deadlines or extension policies should be confirmed with the Amity Online admissions team at the time of enrollment.
Yes. The Amity Online certifications are designed to align with each other. If you have already completed Descriptive Analytics and Data Pre-processing using Python, this Time Series Forecasting certification is a natural next step, building on Python proficiency to cover statistical forecasting models and time-dependent data analysis.
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