• All Courses
  • Teach
  • Blog
  • Login
  • Register
  • Select preferred Language:
  • Development
    • Web Development
    • Mobile Apps
    • Programming Languages
    • Game Development
    • Database
    • Software Testing
    • Software Engineering
    • More...
  • Business
    • Data Analytics
    • Enterpreneurship
    • Finance
    • Big Data
    • Project Management
    • More...
  • Office Productivity
    • Microsoft
    • SAP
    • Salesforce
    • More...
    • OS and Network
    • Marketing
    • Design
    • Personal Development
    • Test Prep
  • All Courses
  • Teach
  • Blog
  • Login
  • Register
  1. Home
  2. Tutorial
  3. Data Science

All courses in: data-science

  • Price low to high
  • Price high to low
  •   English
  •   Hindi
  •   Telugu
  •   Tamil
  •   Free
  •   Paid
En English
Learn By Example: Statistics and Data Science in R

By: Loonycorn A 4-Ppl Team;ex-Google.

235
  • 4 (76)
2495 599
Enroll

Learn By Example: Statistics and Data Science in R

By: Loonycorn A 4-Ppl Team;ex-Google.
235 English
  • 4
2495 599
En English
Data Science, Deep Learning & Machine Learning with Python

By: Frank Kane

150
  • 5 (41)
3992 599
Enroll

Data Science, Deep Learning & Machine Learning with Python

By: Frank Kane
150 English
  • 5
3992 599
En English
Connect the Dots: Linear and Logistic Regression

By: Loonycorn A 4-Ppl Team;ex-Google.

26
  • 5 (6)
1996 599
Enroll

Connect the Dots: Linear and Logistic Regression

By: Loonycorn A 4-Ppl Team;ex-Google.
26 English
  • 5
1996 599
En English
Financial Risk Management in Python, R and Excel

By: Loonycorn A 4-Ppl Team;ex-Google.

26
  • 5 (6)
1999 599
Enroll

Financial Risk Management in Python, R and Excel

By: Loonycorn A 4-Ppl Team;ex-Google.
26 English
  • 5
1999 599
En English
The Comprehensive Statistics and Data Science with R Course

By: Geoffrey Hubona

19
  • 5 (7)
3743 599
Enroll

The Comprehensive Statistics and Data Science with R Course

By: Geoffrey Hubona
19 English
  • 5
3743 599
En English
Connect the Dots: Factor Analysis

By: Loonycorn A 4-Ppl Team;ex-Google.

20
  • 5 (3)
1996 599
Enroll

Connect the Dots: Factor Analysis

By: Loonycorn A 4-Ppl Team;ex-Google.
20 English
  • 5
1996 599
En English
Learn By Example : Qlikview

By: Loonycorn A 4-Ppl Team;ex-Google.

6
  • 5 (2)
1996 599
Enroll

Learn By Example : Qlikview

By: Loonycorn A 4-Ppl Team;ex-Google.
6 English
  • 5
1996 599
En English
Numerical Techniques for Portfolio Optimization

By: Loonycorn A 4-Ppl Team;ex-Google.

23
  • 5 (4)
4000 599
Enroll

Numerical Techniques for Portfolio Optimization

By: Loonycorn A 4-Ppl Team;ex-Google.
23 English
  • 5
4000 599
En English
Show And Tell: Sikuli - Pattern-Matching and Automation

By: Loonycorn A 4-Ppl Team;ex-Google.

7
1999 599
Enroll

Show And Tell: Sikuli - Pattern-Matching and Automation

By: Loonycorn A 4-Ppl Team;ex-Google.
7 English
1999 599
This course prepares you for the role of Data Scientist by making you an expert in Statistics, Data Science, Big Data, R Programming, Python, and SAS.

What is Data Science?

Data science is a multidisciplinary blend of data inference, algorithmm development, and technology in order to solve analytically complex problems. At the core is data. Troves of raw information, streaming in and stored in enterprise data warehouses. Much to learn by mining it. Advanced capabilities we can build with it. Data science is ultimately about using this data in creative ways to generate business value. This aspect of data science is all about uncovering findings from data. Diving in at a granular level to mine and understand complex behaviors, trends, and inferences. It's about surfacing hidden insight that can help enable companies to make smarter business decisions.

Why Data Science?

How do data scientists mine out insights? It starts with data exploration. When given a challenging question, data scientists become detectives. They investigate leads and try to understand pattern or characteristics within the data. This requires a big dose of analytical creativity. Then as needed, data scientists may apply quantitative technique in order to get a level deeper – e.g. inferential models, segmentation analysis, time series forecasting, synthetic control experiments, etc. The intent is to scientifically piece together a forensic view of what the data is really saying. This data-driven insight is central to providing strategic guidance. In this sense, data scientists act as consultants, guiding business stakeholders on how to act on findings. For anyone that wishes to enhance their business/knowledge by being more data-driven, data science is the secret sauce. Data science projects can have multiplicative returns on investment, both from guidance through data insight, and development of data product. Though, hiring people who carry this potent mix of different skills is easier said than done. There is simply not enough supply of data scientists in the market to meet the demand (data scientist salary is sky high). Thus, when you manage to hire data scientists, nurture them. Keep them engaged. Give them autonomy to be their own architects in how to solve problems. A great way of finding your way into a data science or analytics career is through online courses. Here I look at some favorite Data Science online courses.

Other Categories

Business Design Development Marketing Office Productivity OS and Network
About Company

Unanth is an online learning marketplace connecting tutors and students. Our next generation platform helps tutors create and publish courses easier while ensuring high quality learning experience to students.

COMPANY INFO
  • About Us
  • Terms of Use
  • Privacy Policy
  • Copyright Policy
  • Refund Policy
CONNECT WITH US
  • Help Center
FOLLOW US

© 2018 Unanth. All Rights Reserved.