Courses Offered

We are offering Data Science, Data Analyst and Data Engineering Courses

Gist of our Programs: In the era of MOOCs, everything is readily and freely available in the internet. However, the downside is you easily get confused in which one to choose. You can definitely prepare yourself as most of our team did few years back, however, the only caveat is, it will take trail & error and more TIME.

Having passed through all this process already, our team will guide you through the optimized plan and resources to achieve your dream to enter the analytics world ASAP.

Data Scientist vs Data Analyst vs Data Engineer

Data Science

Data Scientist analyses and interpret complex digital data. While there are several ways to get into a data scientist’s role, the most seamless one is by acquiring enough experience and learning the various data scientist core skills and using them to tackle various business problems.

Roles and Responsibilities:

  • Apply quantitative techniques from fields such as statistics, optimization, and machine learning/ deep learning toward the solution of important business problems from different areas of various industries.
  • Use statistical/ML/DL approaches to build predictive models
  • Enable hypothesis decision making by extracting insights from structured and unstructured data sets
  • Identify new data sources and variables to explore their potential use in developing actionable business insights
  • Explore new technologies, tool, and analytic solutions for use in model development
  • Develop customized interactive reports and dashboards 
  • Help maintain and upgrade existing models

Core Skill Set of Data Scientist

Python, SQL, Hadoop, R

Algebra, Statistics, and Probability

Machine Learning and Deep Learning

Data visualization tools: Tableau, etc.

Business acumen skills

Communication skills 

Robust storytelling techniques

Data Analyst

Data Analyst deciphers numbers and translates them into words/visualizations to explain what data tells. 

Landing a data analyst job doesn’t require a strong mathematics background. However, to do well in this role one needs comprehension in statistics, data pre-processing, data visualization (Tableau, Qlikview, Power BI, etc.) and EDA analysis, and proficiency in Excel and SQL. 

Companies expect you to have deep understanding of the business area and presentation skills. Programming (R, Python) and machine learning are desirable but not a must.

Roles and Responsibilities:

  • Analyzing the datasets using descriptive statistics
  • Using database queries to retrieve and manipulate information.
  • Perform testing and validation of data sets
  • Perform data filtering, cleaning, EDA and early stage transformation.
  • Collaborate with team and managers to address data needs for various company projects
  • Communicating results with the team using data visualization.
  • Work with various teams to understand data to improve and streamline their processes
  • Create quality dashboards and KPI reports
  • Document of data structures and types of business data

Core Skill Set of Data Analyst

Data visualization tools  

SQL and Advance Microsoft Excel

Data munging techniques

Data Cleaning & Data Analysis

Statistical Analysis knowledge

Python and/or R good to have

Presentation & Communication Skills

Data Engineering

A data engineer is responsible for designing, building, integrating, testing and maintaining the data architecture. They act as a link between data scientists and data analysts to help them create new insights from data. They need to have a strong technical and coding background with the ability to create and integrate APIs. They need to have good understanding of data pipelines and performance optimization. 

Roles and Responsibilities:

  • Design, develop, test and maintain architectures and processing workflows
  • Build robust, modular and efficient data pipelines
  • Develop solutions for data acquisition and data gathering
  • Ensure data architecture supports business requirements
  • Develop data processes for modeling, mining, and production
  • Drive the usage of new data sources and variables
  • Advocate new ways to improve data efficiency and quality

Core Skill Set of Data Engineer

Ins and outs of SQL/SAS

Database systems/ Data warehouse

Coding ability (Python, Scala)

Designing & integrating data pipelines

Big Data tools hands-on knowledge

ETL solutions

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