Time Series Analysis:Hands-On Projects & Advanced Techniques

Time Series Analysis: Hands‑On Projects & Advanced Techniques – taught by Temotec Learning Academy, is a comprehensive Udemy online course that lets you master time‑series analysis with Python. Updated July 2026, this free‑coupon‑eligible training covers everything from data import to advanced forecasting models. Whether you search for a free time series course, an Udemy course on time‑series analysis, or want to learn time‑series online, this program delivers practical skills and a certification you can showcase on LinkedIn.

What You'll Learn

• Import and clean real‑world time‑series datasets using pandas and NumPy.
• Calculate key time‑series statistics such as moving averages, seasonality, and autocorrelation.
• Create interactive visualizations with Matplotlib, Seaborn, and Plotly to reveal hidden patterns.
• Build ARIMA, SARIMA, and Prophet models for accurate forecasting.
• Forecast future values and evaluate model performance with MAE, RMSE, and MAPE metrics.
• Manipulate multi‑frequency data, handling missing values and irregular intervals.
• Apply advanced techniques like decomposition, stationarity testing, and feature engineering.
• Develop end‑to‑end projects that simulate finance, weather, and sensor‑data scenarios.

Course Details

• Instructor: Temotec Learning Academy
• Rating: 4.8 stars (based on numerous reviews)
• Level: Beginner to Intermediate
• Language: English (en‑US)
• Certificate: Yes, upon completion
• Includes:
  • Lifetime access to all video lectures
  • Mobile‑friendly playback on Udemy app
  • Hands‑on projects with downloadable source files

What This Course Covers

Importing & Cleaning Time‑Series Data

• Load CSV, Excel, and API‑based time‑series files into pandas DataFrames
• Parse dates, set proper indexes, and handle time‑zone conversions
• Detect and fill missing observations using interpolation and forward‑fill methods

Core Time‑Series Statistics

• Compute rolling statistics, exponential smoothing, and differencing
• Perform stationarity tests such as Augmented Dickey‑Fuller (ADF)
• Analyze autocorrelation and partial autocorrelation functions (ACF & PACF)

Visualization Techniques

• Plot line charts, seasonal subplots, and heatmaps for trend detection
• Use Plotly for interactive dashboards that support zoom and hover details
• Visualize decomposition results (trend, seasonality, residual)

Modeling & Forecasting Fundamentals

• Build classic ARIMA and SARIMA models with optimal order selection
• Implement Prophet for business‑grade forecasting with holidays and regressors
• Validate forecasts using train‑test splits and cross‑validation

Advanced Techniques & Feature Engineering

• Apply Fourier transforms and wavelet analysis for frequency‑domain insights
• Engineer lag features, rolling windows, and time‑based categorical variables
• Combine multiple models in ensemble approaches to boost accuracy

Capstone Projects

• Financial market price prediction using historical stock data
• Weather temperature forecasting with seasonal adjustments
• Sensor‑data anomaly detection for IoT applications

Who Should Take This Course

• Beginners and intermediate Python programmers eager to specialize in data analysis.
• Data analysts who need to add time‑series expertise to their analytical toolkit.
• Data scientists looking for practical forecasting models for production pipelines.
• Business analysts tasked with demand planning, sales forecasting, or KPI trend monitoring.
• Financial and AI engineers who require robust time‑series methods for algorithmic trading or predictive maintenance.

Prerequisites

• No prior experience needed — this course is beginner‑friendly.
• A computer with Python 3.x installed and basic familiarity with Jupyter notebooks.
• Recommended (but not required): understanding of basic statistics and Python loops.

Why Enroll in This Course

This Udemy course offers a free coupon that provides 100 % off for a limited time, making high‑quality time‑series training accessible to everyone. The curriculum blends theory with hands‑on coding, ensuring you can apply concepts immediately to real data. Compared with generic tutorials, the course delivers a structured pathway from data import to advanced forecasting, backed by a reputable certification. Act now—today’s free access expires soon, and the skills you gain will stay valuable for years.

Course Highlights

• Lifetime access to all video lessons, quizzes, and project files.
• Self‑paced learning allows you to study whenever and wherever you prefer.
• Certificate of completion to showcase your new time‑series expertise.
• Mobile‑friendly content lets you practice on tablets or smartphones.