Think about a world the place algorithms assist medical doctors diagnose diseases in seconds, self-driving vehicles navigate effortlessly, and devices anticipate our wants earlier than we even ask. Appears like science fiction? As we strategy 2025, machine studying is popping these visions into actuality. From chatbots that maintain human-like conversations to suggestion techniques that know your subsequent favourite film, machine studying powers numerous improvements—and its affect is just rising.
Interested in grasp these expertise? Fixing hands-on tasks is likely one of the finest methods to show curiosity into experience. Listed below are 30 beginner-friendly machine studying tasks to ignite your journey into the AI revolution.
Newbie-Degree Machine Studying Tasks
Newbie-level machine studying tasks are excellent for these beginning their ML journey. These tasks concentrate on easy but impactful issues, serving to you grasp foundational ideas and apply primary algorithms successfully.
1. Home Pricing Prediction
On this undertaking, you’ll want to predict the worth of homes primarily based on options like space, variety of rooms, loos and extra. It supplies an excellent introduction to regression issues. The dataset is relatively small and simple to know. You need to use primary ML algorithms to finish this undertaking.
Downside: Predict the worth of a home.
Begin: Get Knowledge | Tutorial: Get Right here
2. Future Gross sales Prediction
For this undertaking, your job is to forecast the full quantity of merchandise offered in each store utilizing day by day historic gross sales knowledge. Notice that the record of retailers and merchandise barely modifications each month, so you’ll want to create a mannequin which may deal with such a scenario.
Downside: Predict future gross sales primarily based on previous gross sales knowledge.
Begin: Get Knowledge | Tutorial: Get Right here
3. Music (Style) Classification
On this undertaking, you’ll want to use a number of audio information, and the duty is to categorize every audio file right into a sure class like audio belonging to Disco, hip-hop, and so forth. The music style classification will be constructed utilizing completely different algorithms like SVM, KNN and lots of extra. It’s a terrific newbie undertaking for these fascinated by sound classification and sample recognition.
Downside: Classify music tracks into genres primarily based on their options.
Begin: Get Knowledge | Tutorial: Get Right here
4. Mortgage Eligibility Prediction
Utilizing buyer particulars like gender, marital standing, training and so forth., you’ll want to automate the method of predicting whether or not a buyer is eligible for a mortgage or not. It’s a sensible introductory undertaking to binary classification.
Downside: Predict whether or not a mortgage shall be authorized or not primarily based on buyer knowledge.
Begin: Get Knowledge | Tutorial: Get Right here
5. Coupon Buy Prediction
On this undertaking, your objective right here is to develop a classification mannequin with buyer knowledge whether or not they’ll redeem on coupons or not. It’s helpful for the companies to know whether or not a given buyer will redeem their coupon or relatively not redeem the coupon This fashion, an organization will be ready to plan its methods and in addition goal these people who’re prone to redeem a selected coupon. It is a well-known classification drawback.
Downside: Predict if a buyer will redeem a coupon primarily based on their profile.
Begin: Get Knowledge | Tutorial: Get Right here
6. Social Media Sentiment Evaluation
On this undertaking, an effort goes to be made to categorize the textual content from the social media posts into constructive or detrimental and or impartial which is able to then be used to research the emotions of the textual content from the put up made on social media platforms. It allows enterprise companies to know the perceptions of shoppers and consequently arrive at concrete changes to their providers, merchandise, and advertising and marketing methods.
Downside: Classify social media posts into sentiment classes like constructive or detrimental.
Begin: Get Knowledge | Tutorial: Get Right here
7. Churn Prediction
That is certainly a really sensible real-world classification drawback through which the target is to forecast whether or not or not a buyer of a selected agency will proceed or discontinue his use of the service offered by that agency, given the related utilization knowledge. They’re used most steadily in telecom, finance, and e-commerce trade sectors.
Downside: Predict whether or not a buyer will churn primarily based on their interplay with the corporate.
Begin: Get Knowledge | Tutorial: Get Right here
8. Credit score Card Fraud Detection
This is likely one of the finest real-life examples to work with the imbalanced dataset since, in fraud detection, your goal is to foretell whether or not or not a bank card transaction is a fraudster transaction. That is additionally a classification drawback.
Downside: Predict if a bank card transaction is fraudulent or not.
Begin: Get Knowledge | Tutorial: Get Right here
9. Insurance coverage Premium Prediction
From this evaluation, the target of the present undertaking is to estimate the quantity of future medical bills of the purchasers to allow medical insurance coverage to find out fees on premium primarily based on varied attributes as proven beneath; It’s a regression drawback.
Downside: Predict the insurance coverage fees primarily based on private info.
Begin: Get Knowledge | Tutorial: Get Right here
10. Human Exercise Detection utilizing Smartphones
For this undertaking the objective is to make use of the info collected by smartphone sensors and classify human actions like sitting, strolling, operating and lots of extra. It’s a classification drawback and is utilized to health and well being monitoring techniques.
Downside: Predict the kind of human exercise primarily based on smartphone sensor knowledge.
Begin: Get Knowledge | Tutorial: Get Right here
11. Resume Parser
On this introductory NLP-based resume parser undertaking your job is to extract related info from the resumes like identify, cellphone quantity, e mail, expertise, expertise and so forth. You should apply completely different textual content processing and NLP methods.
Downside: Extract and classify key info from resumes.
Begin: Get Knowledge | Tutorial: Get Right here
Intermediate-level machine studying tasks are designed to deepen your understanding of ML methods. These tasks sort out extra complicated issues, introducing ideas like time sequence forecasting, suggestion techniques, and unsupervised studying.
12. Music Advice
For this undertaking, you’ll want to construct a suggestion system to recommend music to the customers primarily based on their earlier music selections. It’s a good introductory undertaking for collaborative filtering and content-based suggestion methods.
Downside: Advocate music primarily based on consumer preferences and previous listening historical past.
Begin: Get Knowledge | Tutorial: Get Right here
13. Inventory Costs Predictor
On this undertaking, your objective is to foretell future inventory costs primarily based on the historic knowledge. It’s a good introductory undertaking for the ideas of time sequence forecasting and lets you be taught to use machine studying in finance.
Downside: Predict future inventory costs primarily based on historic knowledge.
Begin: Get Knowledge | Tutorial: Get Right here
14. Film Advice
This undertaking includes constructing a suggestion system that implies films to customers primarily based on their earlier film rankings. It makes use of collaborative filtering to suggest objects.
Downside: Advocate films to customers primarily based on their preferences.
Begin: Get Knowledge | Tutorial: Get Right here
15. Stock Demand Forecasting
On this undertaking, the objective is to forecast the product demand within the stock primarily based on historic gross sales knowledge. It’s a regression drawback and helps to optimize stock and make data-driven choices.
Downside: Forecast the demand for merchandise primarily based on previous stock knowledge.
Begin: Get Knowledge | Tutorial: Get Right here
16. Rented Bike Demand Forecasting
The objective of this undertaking is to foretell bike rental demand primarily based on time of day, season, climate, temp and so forth., utilizing solely prior rental knowledge. This drawback has vital real-world functions.
Downside: Predict the variety of rental bike trip requests.
Begin: Get Knowledge | Tutorial: Get Right here
17. Buyer Segmentation
In a buyer segmentation undertaking the duty is to group the customers primarily based on the given knowledge like gender, occupation, marital standing, demographics and lots of extra. That is an unsupervised studying drawback and it helps companies to cluster prospects in significant teams.
Downside: Section prospects into completely different teams primarily based on their knowledge.
Begin: Get Knowledge | Tutorial: Get Right here
18. Predicting Vitality Consumption
On this undertaking you’ll want to forecast the vitality demand primarily based on vitality consumption knowledge. That is additionally a major drawback to unravel and helps to handle vitality consumption.
Downside: Forecast the vitality demand.
Begin: Get Knowledge | Tutorial: Get Right here
19. Diagnosing Plant Ailments From Leaf Photos
On this undertaking, you must diagnose plant illnesses solely primarily based on leaf photographs. Fixing this drawback is necessary as a result of diagnosing plant illnesses early can save tonnes of agricultural produce yearly.
Downside: Diagnosing plant illnesses from leaf photographs knowledge.
Begin: Get Knowledge | Tutorial: Get Right here
20. Speech Recognition
For this undertaking, you’ll want to construct a speech recognition algorithm which may efficiently determine easy spoken instructions. This helps corporations to make voice-enabled functions and interfaces.
Downside: Establish the easy spoken instructions.
Begin: Get Knowledge | Tutorial: Get Right here
21. Detect Visitors Indicators
The objective of this undertaking is to create a mannequin which may determine the visitors indicators within the footage. It is a vital classification drawback for companies and introduces you to picture processing methods.
Downside: Establish and classify visitors indicators from photographs.
Begin: Get Knowledge | Tutorial: Get Right here
22. Music Era
For this undertaking you should utilize superior machine studying methods to create music from your individual, utilizing current music information. This undertaking introduces you to generative functions of machine studying.
Downside: Generate new music primarily based on patterns in current music.
Begin: Get Knowledge | Tutorial: Get Right here
23. Language Translation utilizing ML
This undertaking includes constructing a mannequin to translate textual content from one language to a different utilizing machine studying methods. It includes sequence-to-sequence fashions and pure language processing.
Downside: Translate textual content from one language to a different utilizing superior machine studying ideas.
Begin: Get Knowledge | Tutorial: Get Right here
24. Construct a Customized Chatbot
Utilizing NLP and machine studying your job is to create a customized chatbot that may discuss with customers and clear up their queries. It is a good undertaking for studying conversational AI and language understanding.
Downside: Construct a customized chatbot.
Begin: Get Knowledge | Tutorial: Get Right here
Superior-Degree Machine Studying Tasks
Superior-level machine studying tasks problem you to use cutting-edge methods to unravel intricate issues. These tasks usually contain deep studying, generative fashions, and revolutionary functions in areas like laptop imaginative and prescient and pure language processing.
25. Speech Emotion Recognition
This undertaking includes recognizing feelings from speech indicators. It makes use of audio processing and deep studying fashions to categorise feelings like happiness, disappointment, and anger from speech.
Downside: Acknowledge feelings from speech indicators.
Begin: Get Knowledge | Tutorial: Get Right here
26. Market Basket Evaluation
This undertaking focuses on analyzing retail transactions to determine associations between merchandise. It makes use of affiliation rule studying to foretell merchandise which are steadily purchased collectively.
Downside: Establish associations between merchandise in market baskets.
Begin: Get Knowledge | Tutorial: Get Right here
27. License Quantity Plate Recognition System
The objective right here is to construct a strong and automated automotive quantity plate recognition system, which may efficiently determine a plate and acknowledge its quantity. It introduces you to object detection and laptop imaginative and prescient.
Downside: Acknowledge car license plate numbers from photographs.
Begin: Get Knowledge | Tutorial: Get Right here
28. COVID-19 Prediction
This undertaking makes use of historic knowledge and machine studying to foretell the unfold of COVID-19. It includes time-series forecasting and regression methods to foretell future tendencies in case numbers.
Downside: Predict the longer term unfold of COVID-19.
Begin: Get Knowledge | Tutorial: Get Right here
29. Sensible Voice Assistant For The Blind
This undertaking includes creating a wise voice assistant, particularly for blind individuals, which may clarify photographs utilizing speech recognition and pure language processing. It introduces you to constructing voice-based functions for varied use circumstances.
Downside: Construct a wise voice assistant for the blind which may clarify photographs.
Begin: Get Knowledge | Tutorial: Get Right here
30. Hand Gesture Recognition Mannequin
Construct a mannequin that acknowledges hand gestures from photographs utilizing laptop imaginative and prescient methods. It’s a terrific undertaking for understanding picture classification and sample recognition.
Downside: Acknowledge hand gestures from photographs.
Begin: Get Knowledge | Tutorial: Get Right here
Conclusion
From the 30 datasets listed above, begin by selecting one which aligns together with your present talent stage. In case you’re new to machine studying, keep away from diving into superior datasets immediately. Take it step-by-step—don’t overwhelm your self with how a lot you’ll want to be taught. Give attention to regular progress, one undertaking at a time.
When you full 2–3 tasks, showcase them in your resume and GitHub profile (that is essential!). Many recruiters actively assessment GitHub profiles when hiring, so make yours stand out. Keep in mind, the objective isn’t to finish all of the tasks however to pick out ones primarily based on the issue, area, and dataset measurement.
It’s also possible to checkout our AI/ML Blackbelt Plus program which incorporates 50+ guided Machine Studying tasks.
Steadily Requested Questions
A. Newbie-level tasks contain easy duties like regression and binary classification, preferrred for these new to ML.
A. Intermediate tasks improve expertise in time sequence forecasting, suggestion techniques, and clustering methods.
A. Superior tasks provide help to grasp deep studying, generative fashions, and sophisticated real-world functions.
A. They mean you can apply theoretical ideas to unravel real-world issues, boosting technical and analytical expertise.
A. Sure, many tasks embrace hyperlinks to publicly obtainable datasets to get you began.
I am an Synthetic Intelligence fanatic, at the moment employed as an Affiliate Knowledge Scientist. I am keen about sharing data with the neighborhood, specializing in project-based articles. #AI #DataScience #Tasks #Neighborhood