Learning Artificial Intelligence: A How-To Guide
Artificial intelligence (AI) is bringing a sci-fi future to the present. This area of computer science, which aims to allow computers to think and perform tasks like a human, has evolved from an idea…to a chessmaster-defeating computer…to self-driving cars – all in a relatively short period of time. AI has the potential to impact every area of society, and its reverberations are already being felt in unexpected ways.
So, how can you take part in this exciting future?
Learn to Program
The foundations of AI lie in three areas: an ability to program, a basic understanding of machine learning, and a familiarity with bots. Learning a programming language, like Java, Python, Ruby on Rails, or C++ is an absolute necessity to a budding computer scientist – it provides the framework to build anything going forward.
An understanding of machine learning, a field of computer science that teaches computers to ‘learn’ by analyzing data without being specifically programmed by humans to do so, is equally important.
And finally, a familiarity with bots (which combine elements of these things) and how they work is also crucial. Bots are essentially computer assistants, ranging from simple chat interfaces to complex creations like Apple’s Siri or Amazon’s Alexa, that function using the basics of AI.
An understanding of all three of these areas is vital to learning artificial intelligence.
Take a Class
Some computer scientists went to school for their degrees; others are self-taught. Regardless of your education level, taking a class or two on AI can provide a solid understanding of the field. There are multiple online classes offered by prestigious institutions introducing this complex world. Stanford’s “Artificial Intelligence: Principles & Techniques” is one of the best, equipping students with the tools and knowledge to solve daily problems with AI. MIT’s Artificial Intelligence course teaches AI learning methods while breaking down the fundamentals of human intelligence for its students, lending useful perspectives for fledgling computer scientists.
Read about AI
Books and articles are plentiful, and often free resources for programmers of any experience level. Artificial Intelligence: A Modern Approach, by Stuart J. Russell and Peter Norvig, is available online, and offers coverage of the basics. Nils J. Nilsson’s The Quest for Artificial Intelligence is a great history lesson on AI from concept to present. Even Bill Gates has some recommendations on the subject: Nick Bostrom’s Superintelligence and Pedro Domingos’s The Master Algorithm are two of his favorite books about AI.
Tickeron has also created an elaborate online library covering many topics in AI, particularly in regards to the investment field. You can explore the library and blogs from experts on tickeron.com.
Attend Conferences
Conferences are an amazing resource for AI students. Much can be learned from the field’s leading lights as they gather to debate, analyze, and share the results of research and experience. For those who cannot attend a gathering in person, YouTube is full of great archival content from conferences, lectures, and more. It offers the chance to learn directly from some of the most intelligent people in the business, all from the comfort of your couch. Tesla and SpaceX’s Elon Musk has given numerous talks on the subject that novices might find interesting; his 2014 discussion at MIT and 2015 conversation at Samford University provide interesting perspectives on AI in a variety of industries.
Join the Tickeron Community
Tickeron has developed AI for investing. From the novice investor to the expert trader, a user can find AI tools on tickeron.com that can assist in the investment process. Beginners can use Tickeron’s Diversification Score tool to measure how well their current portfolio is diversified. Or, if you simply have cash and are looking for investment ideas, you can query Tickeron’s AI for suggestions.
On a more sophisticated level – but still very much user-friendly – traders can use Tickeron’s Pattern Search Engine, which is an AI tool designed to scan the stock, ETF, cryptocurrency, and forex markets for technical trading patterns. Tickeron’s AI is finding new patterns pretty much every day, and delivering trade ideas right into the inboxes of subscribers. Using Tickeron’s online tools is the equivalent of having an AI assistant, where algorithms do all the work.
The Future
AI has officially entered the mainstream. From ‘Google Now’ on our phones to self-driving cars on the roads to IBM’s Watson besting two previous Jeopardy champions, AI not only exists – it is here to stay. The field holds tremendous untapped potential even as it finds a place in our everyday lives. Use these tips as a guide and join the next generation of computer scientists, who will be instrumental in ushering in AI’s ever-evolving, very bright future.
Contributor
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
TSLA in +2.72% Uptrend, advancing for three consecutive days on October 06, 2026
Moving higher for three straight days is viewed as a bullish sign. Keep an eye on this stock for future growth. Considering data from situations where TSLA advanced for three days, in 263 of 331 cases, the price rose further within the following month. The odds of a continued upward trend are 79%.
Technical Analysis (Indicators)
Bullish Trend Analysis
The Moving Average Convergence Divergence (MACD) for TSLA just turned positive on October 06, 2026. Looking at past instances where TSLA's MACD turned positive, the stock continued to rise in 34 of 46 cases over the following month. The odds of a continued upward trend are 74%.
TSLA moved above its 50-day moving average on September 08, 2026 date and that indicates a change from a downward trend to an upward trend.
The 10-day moving average for TSLA crossed bullishly above the 50-day moving average on September 08, 2026. This indicates that the trend has shifted higher and could be considered a buy signal. In 10 of 15 past instances when the 10-day crossed above the 50-day, the stock continued to move higher over the following month. The odds of a continued upward trend are 67%.
The Aroon Indicator entered an Uptrend today. In 181 of 235 cases where TSLA Aroon's Indicator entered an Uptrend, the price rose further within the following month. The odds of a continued Uptrend are 77%.
Bearish Trend Analysis
The Stochastic Oscillator has been in the overbought zone for 1 day. Expect a price pull-back in the near future.
The Momentum Indicator moved below the 0 level on October 07, 2026. You may want to consider selling the stock, shorting the stock, or exploring put options on TSLA as a result. In 65 of 84 cases where the Momentum Indicator fell below 0, the stock fell further within the subsequent month. The odds of a continued downward trend are 77%.
Following a 3-day decline, the stock is projected to fall further. Considering past instances where TSLA declined for three days, the price rose further in 50 of 62 cases within the following month. The odds of a continued downward trend are 78%.
TSLA broke above its upper Bollinger Band on September 03, 2026. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options.
Fundamental Analysis (Ratings)
The Tickeron PE Growth Rating for this company is 20 (best 1 - 100 worst), pointing to outstanding earnings growth. The PE Growth rating is based on a comparative analysis of stock PE ratio increase over the last 12 months compared against S&P 500 index constituents.
The Tickeron Price Growth Rating for this company is 47 (best 1 - 100 worst), indicating steady price growth. TSLA’s price grows at a higher rate over the last 12 months as compared to S&P 500 index constituents.
The Tickeron Seasonality Score of 50 (best 1 - 100 worst) indicates that the company is fair valued in the industry. The Tickeron Seasonality score describes the variance of predictable price changes around the same period every calendar year. These changes can be tied to a specific month, quarter, holiday or vacation period, as well as a meteorological or growing season.
The Tickeron Profit vs. Risk Rating rating for this company is 72 (best 1 - 100 worst), indicating that the returns do not compensate for the risks. TSLA’s unstable profits reported over time resulted in significant Drawdowns within these last five years. A stable profit reduces stock drawdown and volatility. The average Profit vs. Risk Rating rating for the industry is 92, placing this stock better than average.
The Tickeron SMR rating for this company is 84 (best 1 - 100 worst), indicating slightly better than average sales and a considerably profitable business model. SMR (Sales, Margin, Return on Equity) rating is based on comparative analysis of weighted Sales, Income Margin and Return on Equity values compared against S&P 500 index constituents. The weighted SMR value is a proprietary formula developed by Tickeron and represents an overall profitability measure for a stock.
The Tickeron Valuation Rating of 99 (best 1 - 100 worst) indicates that the company is significantly overvalued in the industry. This rating compares market capitalization estimated by our proprietary formula with the current market capitalization. This rating is based on the following metrics, as compared to industry averages: P/B Ratio (16.260) is normal, around the industry mean (8.703). P/E Ratio (330.972) is within average values for comparable stocks, (493.775). Projected Growth (PEG Ratio) (4.273) is also within normal values, averaging (2.450). Dividend Yield (0.000) settles around the average of (0.017) among similar stocks. TSLA's P/S Ratio (12.225) is slightly higher than the industry average of (2.589).
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