Level: Beginner
🤖 Time Series Forecasting with Python for Machine Learning
Learn to forecast trends using Python and real-world datasets. Build ARIMA, Prophet, and LSTM models, analyze seasonality, and make accurate predictions for business and AI applications.
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3.2k+ learners
Duration
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3.2k+ Enrolled Students
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Includes
• Expert Designed Curriculum
• Doubt Clearing Session
• Forever Community Access
After this course, you can
Understand time series concepts
Train forecasting models
Forecast real-world data
Improve prediction accuracy
Course Curriculum
Expand or explore the full learning path.
Lessons
Start here after enrolling. These lessons form the core learning path for the course.
What Makes Time Series Data Different, and Why Shuffling It Ruins Everything
Trend, Seasonality, Cycles, and Noise: The Four Ingredients of Every Series
Decomposition: Pulling a Series Apart (Additive vs Multiplicative)
Stationarity: What It Means, Why Models Demand It, and How to Test for It
Loading, Resampling, and Plotting Time Series with Pandas
Train/Test Splits for Time: Why the Future Must Stay in the Future
Baselines First: Naive Forecasts, Moving Averages, Exponential Smoothing
Autocorrelation, ACF and PACF Plots, and Reading Them Without Fear
AR, MA, and ARMA: The Building Blocks Explained Simply
ARIMA: Differencing Your Way to Stationarity, Choosing p, d, q
SARIMA: Handling Seasonality Like Monthly Sales Spikes
Fitting and Diagnosing ARIMA Models with Statsmodels
Prophet: Forecasting When You Have a Deadline, Not a PhD
Modelling Trend Changes, Seasonality, and Holidays in Prophet
Lag Features and Rolling Windows: Teaching Models to Look Back
Date-Time Features and Cyclical Encoding: Why December Sits Next to January
Missing Timestamps, Outliers, and Cleaning Messy Real-World Series
Forecasting with Gradient Boosting on Engineered Features
Why Sequences Need Memory: RNN Intuition Without the Scary Math
Inside an LSTM: Gates, Cell State, and What Actually Gets Remembered
Windowing: Turning a Time Series into a Supervised Learning Problem
Building and Training an LSTM Forecaster in Keras
Multi-Step Forecasting: Predicting One Step vs Many, and the Tradeoffs
When LSTMs Win, and When ARIMA Quietly Beats Your Neural Network
Forecast Metrics That Tell the Truth: MAE, RMSE, MAPE, sMAPE
Backtesting and Rolling-Origin Validation: Cross-Validation, Time Edition
Comparing Models Fairly and Picking a Winner
Capstone Brief: Forecast a Real Dataset End to End
Build Walkthrough: Baseline vs ARIMA vs Prophet vs LSTM, With Decisions Explained
Presenting Your Forecast, Its Uncertainty, and Where to Go Next
Live Session Content
This topic will be taught live in an interactive session, allowing you to engage with the instructor and ask questions in real time. While recordings will be available, attending live offers the best learning experience.
Post Session Study Material
This section will be unlocked after the session. You'll get access to exclusive bonus content, additional examples, and on-demand resources to support continuous learning and deeper understanding.
Requirements
What you should have before starting the course.
Basic Python programming knowledge
Familiarity with machine learning
Understanding of data analysis basics
A computer with Python installed
Tools you are going to use
Python
PyTorch
spaCy
TensorFlow
Hugging Face
Learn From Expert Instructor
Meet the mentors leading the live sessions.
Aarav Sharma
Senior Frontend Engineer, StudioLabs
Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.
LinkedIn
Ananya Mehta
Design Technologist, CraftLabs
Ananya blends design and code to help learners ship portfolio-ready projects.
LinkedIn
Kabir Sayed
Frontend Mentor, PixelWorks
Kabir focuses on clean code, accessibility, and practical frontend delivery.
LinkedInYou should join this course if you
Students & Fresh Graduates
Build a strong portfolio
Learn from live mentors
Get feedback on your work
Working Professionals
Upgrade frontend skills
Ship real projects
Join a peer community
Career Switchers
Structured learning path
Hands-on practice
Guided sessions
Freelancers & Creators
Build client-ready sites
Improve delivery speed
Learn modern workflows
What you will get after completing this course
Receive an official course completion certificate
Earn skill-focused feedback from mentors
Showcase your project in the Shattak community
Access lifetime notes and references
Stay connected with instructors for guidance
Completion bonus
Certificate access, community showcase, and lifetime mentor guidance.
Hear From Learners Who've Taken This Course
Honest feedback from learners who completed the live sessions.
4.8
24
Clear structure, solid examples, and a fast pace that keeps you engaged.
Riya Jain
B.Tech, NIT Trichy
4.6
18
Practical sessions with feedback that helped improve my portfolio.
Kabir Singh
Frontend Intern, PixelWorks
4.9
12
Loved the structure and the live walkthroughs.
M
Meera Patel
Design Graduate
Join Our Community, Ask Questions
Frequently Asked Questions
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Basic familiarity with HTML or CSS is helpful, but the course includes beginner-friendly guidance.
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Mentors provide live feedback and follow-up notes during the sessions.
Yes, you can ask questions in the community group and during live office hours.
Shattak courses are primarily self-paced and may include lessons, recordings, assignments, projects, and additional learning resources. Live sessions may also be conducted based on community demand.
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Yes. Shattak has a learning community where you can ask questions, interact with other learners, share your progress, and get guidance from mentors and peers.
Not always. Each course clearly mentions its requirements and the level of experience needed. Many courses are designed for complete beginners.
Yes. You can earn a course completion certificate after completing the required learning materials and submitting the required assignments or projects.
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Simply open the course page and click Enroll. All courses are free to enroll in, so you can start your learning journey without paying upfront.
After enrolling, you will be redirected to your course workspace. From there, you can access your lessons and follow the learning path step by step.
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Depending on the course, you may get access to: • Self-paced lessons • Live sessions based on community demand • Session recordings • Assignments and hands-on projects • Bonus learning resources • Mentor and peer community support • Doubt-clearing and guidance • Course completion certificates
You can ask questions through the learning community and connect with other learners. Depending on the course, you can also receive guidance from mentors and peers.
After completing the required lessons, assignments, and other course requirements, you can submit your work for certification. Once certified, you can access and share your certificate.
If you are an industry professional or expert and want to teach on Shattak, you can apply to become a mentor and create a course or learning experience based on your expertise.
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Duration
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Get Life Time Access
₹0
₹499
100% off
Get Life Time Access
₹0
₹499
100% off