Data Science
Can a Data Engineer become a good Data Scientist?
There is no doubt that a data engineer is equipped with the necessary technical skills and acumen to become a good data scientist – but there is no guarantee to it as the primary skillsets of a data scientist is not only to engineer or transform data ...
What is after Data Science?
The career roadway after Data Science depends largely on the interests of the individual. Post becoming an expert in the field of Data Science if the individual yearns to seek a career in management & business strategy; then he may shift roles and ...
What is the long term goal of a data scientist?
The long-term goal of a data scientist should be to become a subject matter expert in a particular field of data science (be it machine learning, or predictive modelling, etc). This would ensure that the individual has sufficient knowledge and ...
How useful is time series analysis in data science?
The usefulness of time-series data or cross-sectional data in data science depends largely on the objective of the research. For example – analyzing the effectiveness of marketing campaigns does not require time-series data as it is a one-time ...
What is a data science pipeline?
Data Science pipeline depends on the particular business or industry as well wherein data science projects are operated. While in some cases, the entire set of steps starting data collection comes under the purview of the data science pipeline; in ...
What is a Data Analysis pipeline?
A pipeline, in generic terms, refers to the series of steps via which a particular data or input passes through to get processed into the final output. Data Analysis pipeline also follows the same definition as it involves all steps starting from ...
How Machine Learning is important for Data Science?
Machine learning is an integral part of data science and is used to solve many predictive analytics business problems. Any data science problem wherein historical data is used to predict future occurrences requires knowledge and implementation of ...
Where can I practice practical Data Analysis problems?
The key factor in finding practical data analysis problems in the online domain is that the data provided in online practical sites such as https://www.kaggle.com etc. are much cleaner and more manageable; whereas the data in real-world business ...
How much time do I need to learn Python data science?
The typical time taken to learn Python largely depends on the educational background of the student in terms of whether the student has any prior experience in the programming language. The syntax and semantics of Python are pretty similar to any ...
Some tips for the for aspiring Data Scientists.
In order to become a successful data scientist, it is important not to jump the gun and directly development into statistical models and Python/R commands which could simply take inputs and provide the model output. Rather, the process should be more ...
Would it be better to first learn Data Analysis or Data Science.
Data analysis (or a data analyst) and Data Science (or a data scientist) are two different facets of analytics with different objectives, roles & responsibilities. Hence, it is important for the student to first understand the key requirement of each ...
Can I be a Data Scientist without Mathematics and Statistics?
Becoming a successful data scientist without knowledge and acumen in mathematics or statistics is highly improbable as these are the fundamental blocks of data science. All statistical models, optimization algorithms, machine learning algorithms, ...
Do data scientists need to learn web development?
Whether data scientist needs to learn web development or not largely depend on the organization that he or she is working. For larger companies, there are dedicated teams for web development who caters to the deployment of applications to the web; ...
Can I be a data scientist without learning Python?
Data science professionals & aspirants being majorly from statistics backgrounds tend to face certain issues and problems using Python as it is a programming language based on the OOPS concept. They are most comfortable using R as it majorly caters ...
What are the topics covered in Data Science?
The topics covered in Data Science depending upon the level of the course i.e. whether students are enrolling for a basic course or a more advanced course. Basic courses generally introduce the student to concepts of statistics and probability, and ...
Which is better in terms of salary and long term growth in data science and machine learning.
Data science is a more generic stream of study which encompasses data analysis, machine learning, data visualization, statistical modeling, data engineering, business intelligence, etc. Therefore, from the perspective of opportunities, data science ...
Why is data analysis important in business?
Data analysis is important in business to ensure that the same mistakes are not repeated, and the business can tailor in historical performances in designing future strategies and formulating the business plan. Descriptive analysis provides a view of ...
Which of the career option is better full stack developer or data scientist.
Full-Stack developers and data scientists are both extremely promising career paths in terms of future prospects, demand as well as the lucrativeness of the opportunity. However, the road to becoming a full-stack developer is completely different ...
How are Big Data and Machine Learning related?
Big Data and Machine Learning are not two comparable concepts; rather they are complementary concepts that work together to define and implement Machine Learning systems. Big Data refers to the large chunk of unstructured data which is collected from ...
What is the difference between Data Science,Data Analytics and Business Analytics?
Data Analytics, Business Analytics, and Data Science, though different connotations, has a rather thin line of demarcation between them. Data Analytics is primarily based on massaging & harmonizing the back-end unstructured data of the business, and ...
What is the difference between AI,ML and DS?
Artificial Intelligence (AI) refers to the concept wherein machines and systems are enabled to work as human beings using multiple self-learning algorithms such as decision trees, what-if analysis, etc. Machine learning is the most famous method of ...
Is data science better than business analytics?
There’s not much of a difference between data scientist & business analysts in terms of the acquired skillsets & acumen; however, the application of the acquired skills differs. Data scientists deep dive into the technical side of things focusing on ...
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