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Time Series Analysis, Forecasting, and Machine Learning

Python for LSTMs, ARIMA, Deep Learning, AI, Support Vector Regression, +More Applied to Time Series Forecasting
4.7
4.7/5
(577 reviews)
2,357 students
Created by

9.6

CourseMarks Score®

10.0

Freshness

9.9

Feedback

8.4

Content

Platform: Udemy
Video: 22h 26m
Language: English
Next start: On Demand

Top Time Series Analysis courses:

Detailed Analysis

CourseMarks Score®

9.6 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 2/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

9.9 / 10
We analyzed factors such as the rating (4.7/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

8.4 / 10
Video Score: 10.0 / 10
The course includes 22h 26m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 7 hours 03 minutes of 14 Time Series Analysis courses on Udemy.
Detail Score: 9.7 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

Table of contents

Description

Hello friends!
Welcome to Time Series Analysis, Forecasting, and Machine Learning in Python.
Time Series Analysis has become an especially important field in recent years.
•With inflation on the rise, many are turning to the stock market and cryptocurrencies in order to ensure their savings do not lose their value.
•COVID-19 has shown us how forecasting is an essential tool for driving public health decisions.
•Businesses are becoming increasingly efficient, forecasting inventory and operational needs ahead of time.

Let me cut to the chase. This is not your average Time Series Analysis course. This course covers modern developments such as deep learning, time series classification (which can drive user insights from smartphone data, or read your thoughts from electrical activity in the brain), and more.
We will cover techniques such as:
•ETS and Exponential Smoothing
•Holt’s Linear Trend Model
•Holt-Winters Model
•ARIMA, SARIMA, SARIMAX, and Auto ARIMA
•ACF and PACF
•Vector Autoregression and Moving Average Models (VAR, VMA, VARMA)
•Machine Learning Models (including Logistic Regression, Support Vector Machines, and Random Forests)
•Deep Learning Models (Artificial Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks)
•GRUs and LSTMs for Time Series Forecasting
We will cover applications such as:
•Time series forecasting of sales data
•Time series forecasting of stock prices and stock returns
•Time series classification of smartphone data to predict user behavior
The VIP version of the course will cover even more exciting topics, such as:
•AWS Forecast (Amazon’s state-of-the-art low-code forecasting API)
•GARCH (financial volatility modeling)
•FB Prophet (Facebook’s time series library)
So what are you waiting for? Signup now to get lifetime access, a certificate of completion you can show off on your LinkedIn profile, and the skills to use the latest time series analysis techniques that you cannot learn anywhere else.
Thanks for reading, and I’ll see you in class!

You will learn

✓ ETS and Exponential Smoothing Models
✓ Holt’s Linear Trend Model and Holt-Winters
✓ Autoregressive and Moving Average Models (ARIMA)
✓ Seasonal ARIMA (SARIMA), and SARIMAX
✓ Auto ARIMA
✓ The statsmodels Python library
✓ The pmdarima Python library
✓ Machine learning for time series forecasting
✓ Deep learning (ANNs, CNNs, RNNs, and LSTMs) for time series forecasting
✓ Tensorflow 2 for predicting stock prices and returns
✓ Vector autoregression (VAR) and vector moving average (VMA) models (VARMA)
✓ AWS Forecast (Amazon’s time series forecasting service)
✓ FB Prophet (Facebook’s time series library)
✓ Modeling and forecasting financial time series
✓ GARCH (volatility modeling)

Requirements

• Decent Python coding skills
• Numpy, Matplotlib, Pandas, and Scipy (I teach this for free! My gift to the community)
• Matrix arithmetic
• Probability

This course is for

• Anyone who loves or wants to learn about time series analysis
• Students and professionals who want to advance their career in finance, time series analysis, or data science

How much does the Time Series Analysis, Forecasting, and Machine Learning course cost? Is it worth it?

The course costs $199.99.
The average price is $12.6 of 14 Time Series Analysis courses on Udemy.

Does the Time Series Analysis, Forecasting, and Machine Learning course have a money back guarantee or refund policy?

YES, Time Series Analysis, Forecasting, and Machine Learning has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

At the moment we could not find an available scholarship for Time Series Analysis, Forecasting, and Machine Learning .

Who is the instructor? Is Lazy Programmer Team a SCAM or a TRUSTED instructor?

Lazy Programmer Team has created 16 courses that got 48,107 reviews which are generally positive. Lazy Programmer Team has taught 191,318 students and received a 4.7 average review out of 48,107 reviews. Depending on the information available, Lazy Programmer Team is a TRUSTED instructor.
Artificial Intelligence and Machine Learning Engineer
Today, I spend most of my time as an artificial intelligence and machine learning engineer with a focus on deep learning, although I have also been known as a data scientist, big data engineer, and full stack software engineer.

I received my first masters degree over a decade ago in computer engineering with a specialization in machine learning and pattern recognition. I received my second masters degree in statistics with applications to financial engineering.

Experience includes online advertising and digital media as both a data scientist (optimizing click and conversion rates) and big data engineer (building data processing pipelines). Some big data technologies I frequently use are Hadoop, Pig, Hive, MapReduce, and Spark.

I’ve created deep learning models to predict click-through rate and user behavior, as well as for image and signal processing and modeling text.

My work in recommendation systems has applied Reinforcement Learning and Collaborative Filtering, and we validated the results using A/B testing.

I have taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Hunter College, and The New School.

Multiple businesses have benefitted from my web programming expertise. I do all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies I’ve used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases I’ve used MySQL, Postgres, Redis, MongoDB, and more.

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9.6

CourseMarks Score®

10.0

Freshness

9.9

Feedback

8.4

Content

Platform: Udemy
Video: 22h 26m
Language: English
Next start: On Demand

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