Hands-On Data Science: Build Real World Project

Hands-On Data Science: Build Real World Project

Hands-On Data Science: Build Real World Project

Build Real World Data Science & Machine Learning Project Practically

Language: english

Note: 0/5 (0 notes) 236 students  New course 

Instructor(s): Pianalytix .

Last update: 2022-09-23

What you’ll learn

  • Have a great intuition of many Machine Learning models
  • Know which Machine Learning model to choose for each type of problem
  • Implement Machine Learning Algorithms
  • Create supervised machine learning algorithms to predict classes.



  • Basic knowledge of machine learning



We have been able to process such a voluminous amount of data. We are able to analyze and draw insights from this data owing to these advanced computational systems.

However, despite all these advancements, data remains a vast ocean that is growing every second. While the huge abundance of data can prove useful for the industries, the problem lies in the ability to use this data.

As mentioned above, data is fuel but it is a raw fuel that needs to be converted into useful fuel for the industries. In order to make this raw fuel useful, industries require Data Scientists. Therefore, knowledge of data science is a must if you wish to use this data to help companies make powerful decisions.

According to Glassdoor, the average salary for a Data Scientist is $117,345/yr. This is above the national average of $44,564. Therefore, a Data Scientist makes 163% more than the national average salary.

This makes Data Science a highly lucrative career choice. It is mainly due to the dearth in Data Scientists resulting in a huge income bubble.

Since Data Science requires a person to be proficient and knowledgeable in several fields like Statistics, Mathematics and Computer Science, the learning curve is quite steep. Therefore, the value of a Data Scientist is very high in the market.

A Data Scientist enjoys the position of prestige in the company. The company relies on his expertise to make data-driven decisions and enable them to navigate in the right direction.

Furthermore, the role of a Data Scientist depends on the specialization of his employer company. For example – A commercial industry will require a data scientist to analyze their sales.

A health-care company will require data scientists to help them analyze genomic sequences. The salary of a Data Scientist depends on his role and type of work he has to perform. It also depends on the size of the company which is based on the amount of data they utilize.

Still, the pay scale of Data Scientist is way above other IT and management sectors. However, the salary observed by Data Scientists is proportional to the amount of work that they must put in. Data Science needs hard work and requires a person to be thorough with his/her skills.


Who this course is for

  • Beginners in data science


Course content

  • Traffic sign classification
    • Introduction
    • Importing the data and libraries
    • Image processing
    • Building the model
    • Creating model for test set
    • Download the project files
  • Text extraction Project
    • Introduction
    • Importing libraries and data
    • Extracting the test from image
    • Modifying the extractor
    • Creating the extractor app
    • Running the extractor app
    • Download the project files


Hands-On Data Science: Build Real World ProjectHands-On Data Science: Build Real World Project


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