What Does a Data Scientist Do?

A data scientist is an expert of getting hold of meaningful information from analyzing business or workplace data. To rephrase, it means that a data scientist helps to solve problems arising in business through certain steps. These steps are;

1. Before getting into collecting data or analyzing, the data scientists asks accurate questions to get a deeper plunge into the problem.
2. He then looks out for the right data sets and variables.
3. A skilled data scientist collects data in different structures and forms from various sources such as public data or enterprise data.
4. After gathering data the scientist processes the raw form of data into the required format for further analysis. This step comprises of putting data into a clean, uniform and complete form.
5. The data is then stored into an analytic system which can be either statistical model or ML algorithm. In this major part a data scientists get insight of patterns and trends by analyzing and identifying.
6. At this step the data scientist interprets the data to look for the right solutions and feasible opportunities.
7. The data scientist ends his job by grasping insight and securing results to share with the required company or stakeholder.

Course Outline:

Lesson No. 1 | Data Science | Data Science Introduction

Lesson No. 2 | Data Science | Data And It’s Processing

Lesson No. 3 | Data Science | Statistics And Probability

Lesson No. 4 | Data Science | Confusion Matrix

Lesson No. 5 | Data Science | Numpy Introduction

Lesson No. 6 | Data Science | Python VS Numpy

Lesson No. 7 | Data Science | Different Functions On Numpy

Lesson No. 8 | Data Science | ND Array

Lesson No. 9 | Data Science | D-Type Array

Lesson No. 10 | Data Science | Array Indexing

Lesson No. 11 | Data Science | Concatenation

Lesson No. 12 | Data Science | Pandas Introduction

Lesson No. 13 | Data Science | Panda Series Of Object

Lesson No. 14 | Data Science | Pandas Data Frame

Lesson No. 15 | Data Science | Function Application And Mapping

Lesson No. 16 | Data Science | Selection With Loc And Iloc

Lesson No. 17 | Data Science | Data Loading

Lesson No. 18 | Data Science | Handling Missing Data

Lesson No. 19 | Data Science | Hierarchical Indexing

Lesson No. 20 | Data Science | Combining And Merging Datasets

Lesson No. 21 | Data Science | Pivoting long To Wide Format

Lesson No. 22 | Data Science | Matplotlib

Lesson No. 23 | Data Science | Machine Learning Algorithms in Data Science

Lesson No. 24 | Data Science | PCA

Lesson No. 25 | Data Science | Project of DS Example