“Practical Data Science: Analyzing Stock Market Data with R” Using the R programming language, students will have a variety of technical and quantitative analysis techniques in this seminar. As the course proceeds, students will be taught about coding. The PDFs that are attached to each lesson contain all the code. Students should follow along to learn the principles better and to see how simple they are. This course isn’t about teaching you how to trade or disclose top-secret trading techniques; rather, it’s about demonstrating how simple it is to use R to investigate the stock market and generate ideas on your own. The courses are usually available at INR 3,499 on Udemy but you can click now to get 87% off and get Practical Data Science: Analyzing Stock Market Data with R for INR 449.
Who Can Opt for this Course?
- Those who want to develop their R expertise with stock market data
- Those who want to draw their own judgments regarding the marketplace
- Not for individuals looking for simple stock recommendations or undiscovered trading methods
- Not an invitation to trade; given how challenging it is, do your research before risking real money
- There is no guaranty that historical strategies will work in future events.
|Registration Link||Apply Now!|
|Price||INR 2299 (|
|Student Enrollment||2,368 students|
|Instructor||Manuel Amunategui https://www.linkedin.com/in/manuelamunategui|
|Total Student Reviews||361|
- Use R to gain insight and inspiration from stock market data
- Yahoo offers free daily stock market data downloads
- Create visually appealing financial charts
- On stock market data, use fundamental technical analysis
- View entries and exits while exploring trade ideas
- Compare related stocks to learn more information
|1.||Introduction (08 minutes)||What is covered in this class|
|Optional: R Console or RStudio?|
|2.||Downloading Free Stock Market Data with R (12 minutes)||Downloading free daily stock market data from Google|
|3.||Creating Amazing Stock Charts with quantmod (30 minutes)||Creating great charts with quantmod|
|Adding Indicators to quantmod charts|
|Creating an R Markdown file to display all your charts in one document|
|4.||Applying Technical Analysis Indicators (01 hour 48 minutes)||Creating a simple moving average (SMA) from scratch|
|Following the trend with multiple moving averages|
|More insights from multiple moving averages|
|Insight from Common indicators – ADX & VWAP|
|Counter-trend systems – ROC, RSI, CCI, Chaikin Volatility|
|Optional: Counter-trend systems – tweaks|
|5.||Tracking Profit and Loss for Fun! (17 minutes)||Evaluating our trend-following systems|
|6.||Analyzing Stocks in Groups (01 hour 05 minutes)||Evaluating counter-trend systems|
|Safety in Numbers: Basket Analysis|
|Applying correlations to entries|
|7.||Conclusions (30 seconds)||Closing notes|
- Basic knowledge of R
- Access to RStudio or R Console
- Concern for stock market information
Joe Young (5/5): This course was fantastic. R makes analyzing the stock market so much easier than other tools I’ve used, and this course shows exactly how to do it. Also, Manuel does an excellent job of explaining the concepts and code. Something that I wanted from the course that wasn’t in it was how to apply some machine learning to find patterns for trading. Manuel, if you plan on adding to this course, definitely add some machine learning. And if there’s some R package that helps in automatically optimizing parameters for the indicators, that would be great too. Thanks very much for the course. It’s all going to be very useful in my trading.
Pros of Course
- James Sommer (5/5): He also does an excellent job laying out the resources for additional learning opportunities.
- David Chu (5/5): This class is not for beginners, but it is a very good course to learn R using quantmod as an additional tool to analyze the market.
- Sharad Pawar (5/5): I like the way they presented all examples and also provides very good insights into R capabilities.
- Howard (5/5): Very good visuals on R libraries that I didn’t know existed.
Cons of course
- Jacob (2/5): A lot of copy and paste, little to no detailed explanation.
About the Author
The instructor of this course is Manuel Amunategui who is a Data Scientist & Quantitative Developer with a 4.5 Instructor Rating and 1,511 Reviews on Udemy, he/she offers 11 Courses and has taught 48,494 Students so far.
- Data scientist with more than 20 years of experience in the technology sector, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached the top 1% on Kaggle and was given the title of “Competitions Expert,” taught more than 20,000 students on Udemy, and served as vice president of data science at SpringML
- Manuel Amunategui feels like he has seen it all, having worked in machine learning consultancy, healthcare modeling, the financial sector for six years on Wall Street, and Microsoft for four
- And this has made him aware of the enormous need for instructional resources on practical data science
- “It just ain’t genuine until it hits your customer’s plate,” as I like to remark
- As a startup adviser, he is available to talk at businesses and academic institutions about topics like creating and inspiring data science teams and everything related to machine learning
|Parameters||Practical Data Science: Analyzing Stock Market Data with R||Automating Data Exploration with R||Practical Data Science: Reducing High-Dimensional Data in R|
|Offers||INR 455 (||INR 455 (||INR 455 (|
|Duration||4 hours||4 hours||2.5 hours|
|Rating||4.4 /5||4.7 /5||4.3 /5|
|Instructors||Manuel Amunategui||Manuel Amunategui||Manuel Amunategui|
|Register Here||Apply Now!||Apply Now!||Apply Now!|