What you'll get
  • 57+ Hours
  • 16 Courses
  • Course Completion Certificates
  • Self-paced Courses
  • Technical Support
  • Case Studies

Synopsis

  • Designed to build practical expertise in time series analysis and forecasting using Python for real-world applications.
  • Provides one year of full access to self-paced, video-based learning.
  • Open to individuals committed to developing strong skills in forecasting and time series modeling.
  • Requires foundational understanding of Python, data science concepts, and machine learning basics.
  • Includes hands-on projects and course completion certificates across 16 modules.
  • Offers verifiable certificates with unique links suitable for resumes and LinkedIn profiles.

Content

Courses No. of Hours Certificates Details
Python for IoT Tutorials10h 33m✔View Curriculum
Advanced Python for IoT & IoT based Data analysis6h 29m✔View Curriculum
Statistics for Data Science using Python3h 23m✔View Curriculum
Data Science with Python4h 14m✔View Curriculum
Machine Learning using Python3h 26m✔View Curriculum
Courses No. of Hours Certificates Details
Forecasting the Sales of the Store Using Time Series Analysis2h 13m✔View Curriculum
House Price Prediction using Linear Regression3h 2m✔View Curriculum
Predictive Modeling with Python8h 26m✔View Curriculum
Data Science with Python Project-Predict Diabetes on Diagnostic Measures1h 02m✔View Curriculum
Logistic Regression-Predicting the Survival of Passenger in Titanic2h 6m✔View Curriculum
Courses No. of Hours Certificates Details
Project on Linear Regression in Python2h 28m✔View Curriculum
Credit-Default using Logistic Regression3h 3m✔View Curriculum
Financial Analytics with Python1h 6m✔View Curriculum
Courses No. of Hours Certificates Details
Artificial Intelligence with Python6h 15m✔View Curriculum
Sentiment Analysis with Python57m✔View Curriculum
Tensorflow With Python1h 46m✔View Curriculum

Description

Time Series Analysis and Forecasting centers on analyzing historical data to uncover trends and use those insights to anticipate future outcomes. This discipline applies structured methods and programming techniques to identify trends, seasonality, and changes over time. By relying on previously recorded data, organizations can build reliable predictive models that support accurate forecasting. When applied correctly, these analytical approaches enable businesses to recognize emerging trends and make informed, strategic decisions with greater confidence.

Sample Certificate

Course Certification

Requirements

  • This course relies on certain foundational technologies as essential prerequisites.
  • Learners should have a strong understanding of data science concepts, as the curriculum builds directly on data-driven analysis techniques.
  • Prior exposure to data science makes it easier to understand and apply the more advanced modules.
  • Working knowledge of machine learning is important, as several lessons and hands-on projects rely on these concepts.
  • Familiarity with core machine learning principles helps learners progress smoothly through the curriculum.
  • All prerequisite topics are also revisited within the course to provide a complete and convenient learning experience.

Target Audience

  • Created to serve diverse learners who aim to develop strong expertise in Time Series Analysis and Forecasting with Python.
  • Suitable for professionals, trainers, and students seeking to strengthen their analytical and forecasting skills.
  • Ideal for developers or working professionals with experience in Python or other programming languages who want to apply time series techniques in Python.
  • Delivers advanced-level insights to help experienced learners develop a strong, in-depth understanding of the subject.
  • Well-suited for Python learners who wish to explore time series analysis and forecasting from the fundamentals.
  • Valuable for educators looking to deepen their knowledge and enhance the quality of training they provide.