Title: Data Science Vs Machine Learning Vs Data Analytics
1www.simpliv.com
2What is Data Science?
Data Science is a field of technology that
deals with exploring, modeling, and analyzing
the big data to get meaningful insights from
them that can solve a crucial business problem
www.simpliv.com
3Data Scientist Major Responsibilities
- Feature Engineering To prepare the proper input
dataset that is compatible with the requirements
of Machine Learning Algorithm. - Predictive Modeling To predict the outcomes with
the help of data models. These models are used
for predicting various activities, events,
phenomenon, etc. - Machine Learning and Deep Learning Machine
Learning seeks to educate the machines without
human intervention. Deep Learning deals with
artificial neural network which is nothing but
multiple layers of algorithms.
www.simpliv.com
4Skills Required to Become a Data Scientist
- Common Data Science Skills with Data Analytics
Can be divided into Technical and Non-Technical
Data Science Skills. - Common Data Science Skills (Technical)
Programming, Data Visualization - Common Data Science Skills (Non-Technical)
Presentation Communication Skills, Business
Thinking
- Data Science and Data Analytics are quite similar
in broader perspective. - Unique Data Science Skills Can be divided into
Technical and Non-Technical Data Science Skills. - Unique Data Science Skills (Technical) Database,
Statistics Mathematics - Unique Data Science Skills (Non-Technical)
Problem-solving, Data-driven Decision-Making
www.simpliv.com
5Qualification Required to Become a Data Scientist
- Bachelor's Degree in Computer Science, IT, or
Related Field Earning a Bachelors Degree in CS,
IT or any related field will make the journey a
little easier. - Master's Degree in Computer Science or Related
Field Earning a Masters Degree in Data Science
will introduce a candidate to the high-level
programming and integration. - Experience in Related Field Starting-off as an
entry-level Data Analyst, or Data engineer, or
Business Analyst will help you gain domain
acumen, as well as technical expertise.
www.simpliv.com
6What is Machine Learning?
Machine learning is a field that deals with
educating the machines to make them intelligent.
www.simpliv.com
7Machine Learning Expert Major Responsibilities
- Machine Learning Experiments To undertake
various experiments and tests and run them. Fine
tune the test results and implement them. - Train and Retain the System To develop models
that are capable of learning continually from a
stream a data. - Perform Statistical Analysis To select the
appropriate datasets and data representation
methods to run statistical analysis and fine-tune
the test results. - Extend ML Frameworks To work towards extending
the existing ML libraries and frameworks.
www.simpliv.com
8Skills Required to Become a Machine Learning
Expert
- Common Machine Learning Skills with Data Science
Can be divided into Technical and Non-Technical
Data Science Skills. - Common Machine Learning Skills (Technical)
Programming, Statistics Mathematics - Common Machine Learning Skills (Non-Technical)
Presentation Communication Skills
- Machine Learning is quite different from Data
Science. However, there are some shared
attributes between these two domains. - Unique Machine Learning Skills Can be divided
into Technical and Non-Technical Data Science
Skills. - Unique Machine Learning Skills (Technical)
Software Designing, Machine Learning Algorithm,
Computer Science, Data Visualization - Unique Machine Learning (Non-Technical) Working
in Teams, Time Management, Leadership
www.simpliv.com
9Qualification Required to become a Data Analyst
- Earn Qualification
- A Data Analyst needs to acquire either a
Bachelors Degree in - Business related fields.
- Gain Work Experience
- A Data Analyst needs to acquire either a
Bachelors Degree in - Business related fields.
www.simpliv.com
10Data Science vs Data Analytics Which One to
Choose?
Fit for Data Science Fit for Data Analytics
For professionals who are good at problem-solving. For professionals who are good at computation.
Suited for candidates with strong Programming and Data Visualization skills. Suited for candidates with strong Database and Programming skills.
Better suited for people who have worked as BI engineers, business analysts, IT application engineers, Architects, and Data analysts. Better suited for people who have worked as database administrators, data warehousing professionals, QA engineers, and associates in Sales, Marketing, etc.
www.simpliv.com
11Data Science Vs Machine Learning Vs Data Analytics
www.simpliv.com
12Conclusion
Modern technology field is blurring the
industrial boundaries, thanks to the explosion of
data. As the dependence on data growing
immensely, the need for having distinctive fields
for separate uses has become imperative. Data
Science, Machine Learning, and Data Analytics are
three such fields, which have confused aspirants
to a great extent. These slides will give you a
clear picture about the three fields and why
should you choose either of them. Click here to
read the blog
www.simpliv.com
13Start Your Certification Journey with SIMPLIV
NOW!
Visit at www.simpliv.com to LEARN MORE!
Explore Blogs blog.simpliv.com
For queries USA 510 849 6155