DATA SCIENCE with PYTHON TRAINING
About Data Science
Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data.It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, in particular from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization.
Either it is structured or unstructured data, Data Science is a field that encompasses anything related to data cleansing, preparation, and analysis.
Job Responsibilities of Data Science
- Collecting large amounts of unruly data and transforming it into a more usable format.
- Solving business-related problems using data-driven techniques.
- Working with a variety of programming languages, including SAS, R and Python.
- Having a solid grasp of statistics, including statistical tests and distributions.
- Staying on top of analytical techniques such as machine learning, deep learning and text analytics.
- Communicating and collaborating with both IT and business.
- Looking for order and patterns in data, as well as spotting trends that can help a business’s bottom line
DATA SCIENTISTS WORKS ON FOLLOWING LIST OF SKILL SETS AND TECHNOLOGIES
The presentation of data in a pictorial or graphical format so it can be easily analyzed.
A branch of artificial intelligence based on mathematical algorithms and automation.
An area of machine learning research that uses data to model complex abstractions.
Technology that recognizes patterns in data (often used interchangeably with machine learning)
The process of converting raw data into another format so it can be more easily consumed.
The process of examining unstructured data to glean key business insights.
Database Querying Language
SQL, or Structured Query Language, is a special-purpose programming language for managing data held in relational database management systems. Almost all structured data is stored in such databases, so, if you want to play with data, chances are you’ll want to know some SQL
Database management systems
- SQL Server
Statistical Programming Languages:
Statistical Analysis Tools
- R Tool
This data science course will provide you a strong foundation to understand Machine Learning Algorithms like Clustering, Random Forest, Decision Trees, Naive Bayes using R and Concepts of Statistics, Time Series, Text Mining.
At the end of this Data Science training, you should be prepared to take up an exciting job opportunity in the field of Data Science
On successful completion of the course, candidates will be able to:
- Analyze Big Data using R, Hadoop and Machine Learning.
- Understand the responsibilities of a Data Scientist
- Understand the use of machine learning algorithms in R
- Learn about the processes involved in the Data Analysis Life Cycle
- Learn how to use data formats including XML, CSV and SAS, SPSS
- Transform data using best practices and tools
- Learn to implement various Data Mining techniques
- Analyse data using Hadoop Mappers and Reducers
- Follow best practices in data visualization and optimization techniques
Following Professionals are recommended for Data Science Training.
- Systems Analysts and programmers interested in expanding their role as a Data Scientist
- ‘R’ professionals who want to captivate and analyze Big Data
- Hadoop Professionals who want to learn R and ML techniques
- Entry-level Data Analysts wanting to understand Data Science methodologies
- Hadoop Professionals who want to learn R and ML techniques
- Non-IT professionals aspiring to get into Data Analytics.
- SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
- Business and data analysts looking to add big data analytics skills, & to understand Machine Learning (ML) Techniques
- Managers of business intelligence, analytics, or big data groups
- College graduates considering data science as a career field
- Information Architects who want to gain expertise in Predictive Analytics
Data Science is a booming demand for skill across industries, which is suited for all individuals at all levels of experience.
Numaware Trainings provide completely practical and real time DataScience Training starts from basics to advanced modules. Get an introduction to the fundamentals of DataScience and gain proficiency in identifying terminologies and concepts in the DataScience environment
Give Miss Call to +91-9916-566-300 for further more details on DataScience Training
Detailed Course Content
- Language Popularity
- Job Trends
- Areas where Python is used.
- Companies using Python and Examples.
- History of Python
- Compiled and Interpreted Languages.
- Why Python as hybrid language.
Installation – Python.
- Versions (2.7+ vs 3.0+)
- Available IDEs, Comparison
- Installation of Python and pyCharm.
- IDLE and the interactive shell.
- Basic operations on the shell.
- Running the script file.
Python Data Types
- Strings (Slicing)
- Variable Assignments
- Arithmetic Operators
- Relational Operators
- Logical Operators
- + (Plus)
- * (Multiplication)
- If Statement (elif, else)
- for Statement
- while Statement
- break and continue Statement
- pass keyword
- List Comprehension
- Dictionary Comprehension
- Nested Comprehension
- Definition and calling a function
- Pass by Reference vs Value
- Functions Arguments (Required, Keyword, Default, Variable Length)
- Anonymous (lamda) Functions
- Return statement
- Scope of Variables (Global vs Local)
- Unpacking Arguments
- Args and kwargs.
- Reading Keyboard Inputs
- input function
- Opening and Closing Files.
- Reading and Writing Files.
- Search Path
- Globals() and locals()
- Dir() function
- Packages (Basics, Importing from packages, examples)
- Classes and objects
- Init function
- Class vs Instance Variables vs Static Variables
- Multiple Inheritance
- Standard Exceptions
- Try-finally, except
- Raising an Exception
- Custom Exception
- Min, Max and Sorting on collections/classes
- Bitwise Operators
- What are Regular Expressions
- Matching Characters, Searching
- Compiling Regular Expressions
- Ignore case vs normal search
- Emails Example
- Group Extraction
- Connecting to Database Server
- Connecting to different databases like Mysql/SQLite
- CRUD Operations
- Transactions Management
- Introduction to Threads
- Thread Creation
- Locking Mechanisms
- Different ways of calling threads, class vs functional approach
Introduction Data Science
- Introduction to data science packages,
- Using numpy and pandas
- Reading CSV files
- Extracting Data from CSV files.
Introduction to Web Programming
- Client Server Model
- Request – Response Model
- SOAP vs REST
- CRUD Operations in REST
- Understanding XML and JSON
- Parsing XML
- Parsing JSON
- Introduction to Beautifulsoup Package
- Web Scrapping finance data from Yahoo/Google website
- Download images from web
Introduction Network Programming
- Server & Client – Basics
- File Transfer
- Chat Server and client
DATA SCIENCE TRAINER DETAILS
|Role||:||Data Science Solution lead|
|Experience||:||15+ Yrs of IT Experience across MNC Companies|
|Technologies||:||Data Science, SAS, R , Python, Machine Learning, Advanced Analytics, Bigdata..etc.|
Data scientist solution lead with a demonstrated history in leading development of data science solutions and nearly 15 years of experience in Solution Architecture, Business Analysis, Data Analysis, Software Design, Analysis & Development. Skilled in Machine Learning statistical data analysis, predictive modeling, neural networks and text mining. Plays key role in Analytics team to help the business in improving customer satisfaction and reduce operation costs through data driven techniques.
|Certifications||:||SAS Certified Data Scientist
Certified R Programmer from Advancer
|Role||:||Senior Technical Analyst|
|Experience||:||9+ Yrs of IT Experience across MNC Companies|
|Technologies||:||Data Analytics, Data Science, R, SQL, Hive SharePoint Server, Azure Machine Learning|
|About Trainer||:||Data Scientist with 8 years of hands on experience in Machine Learning and data analytics tools SAS, R, MySQL, Python, Hadoop and Tableau. Currently working with various data owners and data stewards from Finance, Healthcare Quality, Customer Quality, Markets and IT to understand and drive delivery of data management objectives. Training on Various intermediate and advanced levels topics in data science analytics using R for corporate Companies and Clients. Passion about data analytics and solving the complex issues in business using advanced data analytics.|
|Certifications||:||MCSA Machine Learning
MCTS- Microsoft Office SharePoint Server 2007 Application Development
Microsoft Office Specialist – Excel 2010
We support! You Certify
Numaware Technologies provides certification trainings and also support you with getting certified in desired skill sets.
Imp Note: There are no universally required or accepted certifications in the world of data science and/or analytics.
Data Science is a combination of technical skill and Soft Skill to turn data in to actionable sight. Data science is a “concept to unify statistics, data analysis and their related methods” in order to “understand and analyze actual phenomena” with data. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, in particular from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization. The best way to become a data scientist or analyst is to gain the requisite skills and develop a history of showing how you added value with those skills.
Languages or skills like SQL, Python, R, SAS are elementary to become a data analyst or data scientist and below are the few some data science certifications that are widely recognized by industry:
Cloudera Certified Professional Data Scientist
The CCP Data Scientist is geared toward data scientists who can design and develop scalable and robust solutions for production environments. Candidates need to pass three exams: Descriptive and Inferential Statistics on Big Data, Advanced Analytical Techniques on Big Data, and Machine Learning at Scale. Each exam is a challenge scenario, and you are given eight hours to complete it. All three exams must be taken within 365 days of each other.,
CCP certifications are valid for three years.
For more info, click on following link www.cloudera.com/content/cloudera/en/training/certification/ccp-ds.html
SAS Certified Data Scientist
The following list of exams are srerequisite to complete the SAS Certified Data Scientist.
- SAS Certified Big Data Professional
- SAS Certified Advanced Analytics Professional
Candidates for the Data Scientist certification should have deep knowledge of and skills in manipulating big data using SAS and open source tools, using complex machine learning models, making business recommendations, and deploying models. Candidates must pass five exams to earn the SAS Certified Data Scientist credential. The data science certification program comprises the focus areas of both the SAS Certified Big Data Professional and the SAS Certified Advanced Analytics Professional programs, including:
SAS “versioned” Certificates, such as the SAS Certified Data Scientist Using SAS 9, do not expire.
Dell EMC Data Science Associate
The Dell EMC Data Scientist Associate (EMCDSA) is a foundational certification that exposes you to the basics of big data and data analytics. Topics for this certification include an introduction to data analytics, characteristics of big data and the role of data scientists. Also covered are a variety of big data theories and methods, including linear regression, time-series analysis and decision trees.
This exam focuses on the practice of data analytics, the role of the Data Scientist, the main phases of the Data Analytics Lifecycle, analyzing and exploring data with R, statistics for model building and evaluation, the theory and methods of advanced analytics and statistical modeling, the technology and tools that can be used for advanced analytics, operationalizing an analytics project, and data visualization techniques. Successful candidates will achieve the EMC Proven Professional – Data Science Associate credential.
Trainings and Batches
Mode of Training
Numaware provides the following list of trainings according to Trainee or Colleges or Organization preference
- Classroom Training
- Online Training
- Corporate Training
- Campus Training
- University Training
- Virtual Instructor-Led Training
- Instructor-led Live Classroom Training
We are Flexible with following list of batches as per the student requirements and availability.
- Regular Batch
- Weekend Batch
- Weekday Batch
- Fast-Track Batch
- One to One Batch
- Customized Batch
Numaware providing Flexible timings to schedule the Batches according to student-preferred timings at either Morning or Evening
- Morning : 6.00 AM to 12.00PM
- Evening : 3.00 PM to 10.00PM
We Charge very nominal, least and best price for all trainings when compared to Market or any other institutes with good quality standards and no compromise on commitment of providing Quality of Training.
Digital and Flexible Payment Options are available with Numaware Technologies Pvt. Ltd
- Cash with Invoice
- Credit-Card Pay
- Debit-Card Pay
- Any Digital-Pay
- Account Transfer
- Pay-Tm Transfer
Note: Fee will be finalized after demo session as per the Trainer suggestions and Student requirement.
Numaware Technologies Pvt. Ltd is one of the best training institutes in Bangalore, offering Job demanding IT courses, Niche skills for working professionals, fresher’s, and students to ensure a successful future. We offer 100% placement support, cost-effective courses, real-time project experience, resume support, interview support and more. Our courses will equip you to get jobs in top MNCs and launch a successful career.
TRAINING BENEFITS in Numaware Technologies :
- Training with IT Industry experts and Certified professional s working in MNC Companies.
- Importance given to both theory and practice
- Hands-on experience in real-time projects
- Assistance in all stages of getting a job
- Proven track record
- Limited students in a batch
- Flexible timings
- Certification support
STUDENT BENEFITS in Numaware Technologies:
- Post-training and on-job support
- Backup classes for missed sessions
- Remote lab facility, Wi-Fi access and LED TV projection
- Mock exams and interviews for real-life simulation experience
- Affordable fees with 2 easy installments
PLACEMENT BENEFITS in Numaware Technologies:
- Our recruitment team will send you for interviews till you get placed
- Frequently asked interview Q & A will be shared
- Resume build support from industry professionals
- We train you with real cases studies for interviews
- Emphasis on practical knowledge in everything
Numaware Trainings is a Platform for Learning Technologies
Learn what really matters
Just work hard and focus on your job… because luck truly favors the prepared!!
All the best for your career
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