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What can you achieve in 1 year, if you start learning Data Science today?

Beginner Data Science Projects

Data Scientists can sense the pulse of the entire world at any given moment. Data and numbers uncover things like psychological traits of customers, stock market trends, and flaws in the production process of a spacecraft. 

Reaching mastery in Data Science is a process that requires a lifelong commitment to the matter. That is a fact.

But completing a Data Science project can be done with 8-12 months of hard work and dedication – and land you a job as a junior.

Are you wondering if you could do it?

We broke it down – What can you achieve in 1 year, if you start learning Data Science today?

 

Data Science Bootcamp – Final Project: Computer Vision Model | Team 1

Team 1: Computer Vision Model

A team comprised of 2 finance professionals, 1 student, and 1 project coordinator, developed a Computer Vision model that recognizes people with and without masks in real-time and determines their age. It can be implemented in any surveillance system, to identify compliance in real-time. From creating the dataset to training the model and using Python, Jupyter Notebook, Keras, TensorFlow, NumPy, OpenCV, these Data Science beginners got a big ROI on their 12-month investment in skill development. Read more about the project. 

 

 

Team 2: NLP Chatbot

Natural Language Processing is all around us, as auto-correction, text translation and prediction, email filters, smart assistants, digital phone calls, search results, and more. A team comprised of 2 students and 2 mentors created Rubik – Brainster’s new NLP virtual assistant. From creating a dataset of 3000+ questions to implementing a back-end structure and Machine Learning algorithms this group created an advanced technology that can be implemented in businesses across various industries. Read more about the project.

 

Start learning Data Science while working on real projects.

Team 3: Another Computer Vision Model

This group worked on the same Computer Vision model that detects age and wearing a mask. In the end, both teams reached a similar result using a different method. They created the dataset by collecting Internet data, combined with GANs. Then they used a special code to add masks to the generated images. They used Keras and TensorFlow for the model architecture and got the best results with ResNet152. Read more about the project.

 

Ivona from the Data Science Bootcamp is the new reinforcement for the Slovak company i.ERP

Team 4: ML Bank Marketing

A team comprised of finance professionals created a model based on Machine Learning. The dataset was based on historical data from the customer list of a Portughese bank. The purpose of the model is to predict whether a particular client will sign a deposit agreement or not. If the telemarketing campaign was to be reactivated, it would target customers who would most likely deposit funds. Read more about the project.

 

Hard work pays off, and pursuing a career in Data Science is a rewarding journey.

Start learning Data Science while working on real projects. 

 

Team 5: BI analysis

To prove how great the BI possibilities are, Filip and Aleksandar, students from our Data Science Bootcamp, made a detailed data analysis to objectively solve one of the biggest sports dilemmas of Today – Who is the basketball G.O.A.T between Michael Jordan and LeBron James, at the moment when most needed? Read more about this project.

Who is the greatest basketball player of all time The answer lies in the data

What do you want to be when you grow up?