Data Science Analysis

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Amazon is a prime example of just how helpful data collection can be for the average shopper. Amazon’s data sets remember what you’ve purchased, what you’ve paid, and what you’ve searched. This allows Amazon to customize its subsequent homepage views to fit your needs. For example, if you search camping gear, baby items, and groceries, Amazon will not spam you with ads or product recommendations for geriatric vitamins. Instead, you are going to see items that may actually benefit you, such as a compact camping high chair for infants.

Similarly, data science can be useful for reminding you of habitual purchases. If you order diapers every month, for example, you might see a strategically placed coupon or deal around the same time each month. This use of data is meant to act as a trigger, prompting you to think, “I just remembered I need to buy diapers, and I should buy them now because they are on sale.”

WHO CAN LEARN?

  1. Students following mathematics and statistics disciplines as their specialized subjects in graduation or post-graduation can think of a career option of being a data scientist. The job profile for them could be statistician/mathematician or metrics and analytics specialist.
  2. For the computer savvy people, a branch or could say an extension of data science is big data analysis or machine learningand can be entitled as big data analyst or machine learning expert.
  3. For those having knowledge of business domain can also pursue data science as a discipline and can have job titles of business analyst or market research expert.

WHAT WILL YOU LEARN?

  1. Python For Data science Introduction
  2. Data Structures
  3. Functions, Numpy
  4. Matplotlib, Pandas
  5. Statistics- Descriptive
  6. Statistics- Inferential
  7. Machine Learning
  8. Classification Algorithms
  9. Linear Regression
  10. Support Vector Machines, Decision Trees , Random Forest
  11. Clustering
  12. Kmeans
  13. Neural Networks
  14. Tensorflow And Keras
  15. Code implementation
  16. Convolutional Neural Nets
  17. CNN Continued
  18. RNN
  19. Live Project

WHAT ARE LIVE PROJECTS?

During the course of the program, every trainee will be given the opportunity to apply their knowledge learnt in the training on ongoing projects for brands.

BENEFITS OF LIVE PROJECTS?

Before stepping into the professional world of Data Science, a trainee, will already have a first hand experience of how things work in the industry.

HOW DOES IT WORK?

Our trainees will be responsible to handle the Data Science of an existing company/brand provided by Syzygy. The professionals will be guiding and assisting the trainee throughout the entire process.

WHAT CAN YOU OPT FOR AFTER THE TRAINING?

  • Data Architect
  • Business Intelligence (BI) Developer
  • Applications Architect
  • Infrastructure Architect
  • Enterprise Architect
  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Machine Learning Scientist
  • Machine Learning Engineer
  • Statistician

Data science experts are needed in almost every field, from government security to dating apps. Millions of businesses and government departments rely on big data to succeed and better serve their customers. Data science careers are in high demand and this trend will not be slowing down any time soon, if ever.

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