Career in Data ScienceGet ready for next revolution

Data Science

Machine Learning

Artificial Intelligence

Data science includes Machine Learning and AI

A non-natural system who can do any

meaningful work that requires a decision

making

Any system other than natural ones, who can

learn and improve their decision on their own

Application of machine learning on data to

achieve your goals and objectives it is data

science

Open for experts of all domains

• Mathematics and Statistics

• Computer Science & Engineering

• Data Science

• Economics and Social sciences

• Natural Science

Data Science Jobs

Data Science Jobs

• Data Scientist

• Data Analyst

• Data Architect

• Data (Mining) Engineer

Related Jobs

• Business Intelligence Analyst

• Business Intelligence Developer

• Web and UI Developer for ML

• Cloud Engineer for ML

Data Mining Engineer

Data Architect

Data Analyst

Data Scientist

Data in context of Business Goals and Problems

Data Scientist

Data Analytics and ReportingData Analyst

Data MiningEngineer

Data Architect Analyse, integrate, centralize and maintain all data

Manage Database systemsGathering and pre-processing data

Data Scientist

• Discover a hidden insights with the unknown aspects of data

• There is no specific hypothesis

• Go through large amounts of data both structured and unstructured.

• Overall strategy of handling data and using it for business goals

• Pick right and important problems to analyze and address

• Many overlapping skills• Business domain understanding

• Big data systems like Hadoop, Spark

• ML/data processing programming skills like Python/R

• Database Engineering and ETL tools

• Statistics / data mining

Translate a business case into an

analytics agenda,

Develop hypotheses

Understanding Data

Develop impact measurements

metrics

Find, clean, and organize data

Develop models

Measure performance and

impactDeploy models

What is role of a data scientist?

Senior Data Scientist

• Business goal oriented to resolve highly complex business problems

• Be aligned with current needs but must anticipate for future needs and develop strategies and vision to meet those needs

• Innovative in using statistical data and developing new tools to develop analyze data.

Data Analyst

• Focused on a set of data identified by a data scientist or top management

• Transform and manipulate large data sets to suit the desired analysis for companies.

• Compilation and analysis of data to get analytical insights

• Convert data into reports to meaning business and visualization

Get hypothesis of business

goal or issue

Get/gather data for

processing

Understanding Data

Find, clean, and organize

data

Develop analytics and

modelsGet insights

Reports and visualization

What is role of a data analyst?

Data Architect

• Analyse, integrate, centralize and maintain all data

• Work closely with other stakeholders and data providers

• Secure data and control its access

• Improve data quality and eliminate redundancies

Data (Mining) Engineer

• Manages database systems (database administrators)

• Expert in database systems, SQL, ETL tools and Big Data

• Source data internally and externally

• Preprocesses, aggregates and segregates data and makes it meaningful and usable

• Providing real time data streams and batch data to analysts and data scientists

Business Intelligence Analyst

• Analyze internal and external business trends

• Discover insight into past data for meaningful reporting

Business Intelligence vs Data Analysts

BI Analyst

• Interprets past data to facilitate the end-users’ understanding

• Reporting or post-facto (descriptive) analytics

Data Analyst

• analyzes the past data to make future predictions

• Predictive or Prescriptive Analytics

Business Intelligence Developer

• Analyze past data and develop meaningful reports

• Use visualization to facilitate improved end-users’ understanding

Technologies (Our Expertise Only)

• Programming: • Python / R • SQL • Java

• Classical Machine Learning• Scikit-learn• NLTK

• Deep Learning• Keras/TensorFlow• PyTorch

• GUI Tools• Weka, Orange, Knime

• Data Visualization: • Tableau • D3.js • Python / Java / R libraries

• Big data platforms: • AWS• MongoDB • Microsoft Azure

• Other tools• Excel for data science

Career Transition

Domain experts without programming skillsBecome a Data Analyst

Data science is not just about programming, it is only a part of it

You will be most suited to get best of out of data

Data science is changing the world.

You often wonder!

You are not a programmer in the IT world.

Is it for you?

Now, GUI tools have evolved a lot

• GUI tools are intuitive

• They cover wide range of business needs

• They allow you to concentrate on solution to business needs

• Your business intelligence will get best out of these tools

• Many major GUI tools and platforms are available

• Microsoft Azure

• IBM Watson

• Amazon AWS

• SAS

• Weka

• and many more…

Domain experts advantage

• You understand more about data and business needs

• You can discover hidden insights better than others

• Learning a tool is easier than getting domain expertise

• Visualization ideas will come naturally to you

A domain expert

Start with GUI tools

Learn Jupyter Notebook

Data Visualization

Learn working with ML in Cloud

Progression in ML for domain experts

UI designers and Microservices DevelopersBecome Web and UI Developer or Cloud Engineer for ML/Data Science

Leverage your visualization and creativity to gain upper hand

Work with ML/Data Science in cloud

Data Science for Web Developer and UI Designers

• Microservices & UI• Develop end points for ML systems and trained models

• Develop end point for data streaming and processing

• Cloud• Manage and deploy trained models

• Develop and deploy web/mobile apps for end users

• Visualizations• Impactful presentation of data visualization

Data Science for Web Developer and UI Designers

ML Models, Systems and Data Sources

Microservices for data and ML

models

Web and mobile apps for end users of ML

Cloud deployments

Impactful presentation of

data visualization

R/Python/Java ProgrammersBecome a Data Analyst

You have already got advantage

Data Science for R/Python/Java Programmers

• You already have an advantage

• Get started with basic concepts of machine learning

• Start working with classical ML and progress to deep learning

• Learn data visualization tools like Tableau

• Learn how to work with ML in cloud

Data Science for R/Python/Java Programmers

Python/R/Java

Learn basic ML

concepts

Classic ML

Deep Learning

Visualization

ML in Cloud

Database Admins and DevelopersBecome a Data Architect / Data Engineer

Data is natural to you. Deep learning needs lot of data and you know how to get it

Data Science for Database Admins and Developers

• Get started with basic concepts of machine learning

• Progress to deep learning – learn how to use you database skills to your advantage

• Focus on making data relevant, meaningful, non-redundant

• Master pre-processing and data-streaming for ML/Data Science

• Learn use of SQL, ETL tools and Big Data in ML/Data Science

• Learn data security and control issues with ML in cloud

• Data visualization will be logical progression to your skill-set

Data Science for R/Python/Java Programmers

Database Admins

and Developers

Learn basic ML

concepts

Deep Learning

Data Pre-processing

Data Security and Streaming

Visualization

ERP ProfessionalsSAP, Oracle ERP etc

Become a Data Analyst

Data Science for ERP Professionals

• Concentrate on business issues and goals

• Learn classic machine learning and deep learning

• Use GUI tools to speed up learning

• Focus on data visualization in most meaningful way

• Learn how to integrate your ERP modules with ML models and solutions

• Learn how to work with cloud and your ERP modules

Data Science for R/Python/Java Programmers

ERP Professionals

Learn ML concepts

Deep Learning

Data Visualization

Integration of ERP and ML/Data Science

Cloud and you ERP

Thank You