What is data science?
In the simplest terms, data science is a combination of data mining and computer science.
Since the invention of the first computer, data has been continuously generated. Initially, the company relied on data mining, which simply meant generating new information. But in today’s environment, websites and applications are not just brochures, but also bulletin boards or online notification tools. Now, they have become a medium for millions of users to come together and share experiences. Users are now interacting with the website, creating content, comments, likes, research, etc. All of this has led to the creation of large amounts of data, and these companies want to use this data to add more value to their products.
In 2010, the term “big data” was created for the large amount of data that exists around us, and it paved the way for the rise of “data science”, which can gain insights from huge unstructured data sets to Support business. Current and future data science is all about data collection, analysis and modeling. However, the most important part is its applications, such as machine learning, which makes it possible to make machines more precise through data-driven methods; and deep learning has become a machine learning class that has changed our daily lives. And the way we experience things.
The work of industry data scientists
- set: The most important job of a data scientist is to collect data from various sources.
- Exploration and transformation: In order to clear the anomalies that exist in the data, it is necessary to clean and transform the structured and unstructured data.
- analysis: This is the core part of the work. Based on the converted data, the data scientist tries to understand indicators such as what the user is doing or watching and the reason for their departure, and then provides a logical solution, such as what measures can be taken to attract more users and provide them with more Good experience.
- Learning and optimization: A / B testing allows data scientists to experiment with various models and check which model works best.
- Representation and visualization: The whole task is not to create advanced models, but to keep things simple in a way that customers and others can understand.
- Artificial intelligence and machine learning: This is the final part of the task. Data scientists use sophisticated algorithms and machine learning principles to improve the performance of machines on specific tasks.
What can you learn from online training in data science?
Data science is all about using statistical data, creating code, developing models, and ultimately solving problems. To achieve this goal, the focus of the training is to provide in-depth training for students with the following tools:
Hadoop, MapReduce and Spark are used to process data.
The SQL programming language is used for programming and designing database systems.
Python is the most powerful language in machine learning.
R and Excel are very helpful in analysis and data modeling.
Other important tools are SAS, Minitab and XL Miner.
The online training covers all the important concepts mentioned above and provides students with the opportunity to carry out on-site projects. After the training is completed, internship opportunities can also be provided to help students find jobs in leading companies.