Advanced Data Science Training Institutes for Career Growth

Discover how advanced data science training institutes can supercharge your career. Learn cutting-edge skills effortlessly, setting the stage for a successful journey in the evolving field of data science.

Given the quickly increasing field of data science, staying ahead of the curve is essential for career growth. As data becomes increasingly integral to decision-making across industries, the demand for skilled data scientists with advanced expertise is on the rise.

The Evolution of Data Science Education:

• Discuss the shift from foundational to advanced data science education.

• Explore how industry demands have led to the development of specialized, advanced training programs.

Key Components of Advanced Data Science Training:

• Delve into the specific skills and topics covered in advanced training programs.

• Highlight the importance of machine learning, deep learning, and other advanced techniques.

Choosing the Right Institute:

• Provide a guide on factors to consider when selecting an advanced data science training institute.

• Compare renowned institutes and their unique offerings.

Which institute is best for data science?

DV Analytics is considered as the Best Data Science Training Institute in Bangalore which offers services from training to placement as part of the Data Science training program with over 1600+ participants placed in various multinational companies including ANZ, One Saving Bank, Citibank, HSBC,Honeywell , Standard Chartered Bank, Societe Generale, etc. DV Analytics imparts the best Data Science training in Bangalore and is considered to be the best in the industry.

Advanced & Analytics Courses in Dv Analytics

Excel VBA Programming

Visual Basic for Applications. It’s a programming language that enables you to control just about everything in Excel. You’ll learn how to create Macros that can be run from things like a button on a spreadsheet.

COURSE CURRICULUM

SESSION – 1

• Excel navigation through developer tab

• Record the first macro using manual process

• Get through excel vba .notation

SESSION – 2

• VBA conditional logic using If then Else if

• Conditional and logical operators

• Programming Loops and Arrays

• String Functions VBA

SESSION – 3

• Subs and Functions

• VBA code for data importing and connection to db

• Advanced VBA queries for sheet navigation and filters

SESSION – 4

• Excel VBA user forms

• Excel VBA Charts, Embedded Charts, Charts and User Forms etc

SAS Base and Advanced Programming

SAS (Statistical Analysis System). SAS is a business application software which is used for DBMS and reporting, visualization and data mining purposes. To begin with SAS we must start with SAS data manipulation using SAS programming.

SESSION – 1

• SAS Jargons and navigation though SAS PC ad SAS EG windows

• Create first dataset using cards and Datalines

• SAS programming step. SAS libraries/datasets and variables followed by criteria

• Get familiar with sas data types and reading sas into sas using proc import and export, infile and file statement. Connecting to database using proc SQL connect

SESSION – 2

• SAS Library and Datasets descriptions

• SAS options and statements using keep,drop,rename and where etc

• If then and then do statement

• SAS user defined formats. Data transposing using SAS

SESSION – 3

• SAS vertical join- appending tables and scenarios

• SAS joins and relationships. SAS merging vs SAS SQL join

• SAS fact and dimension table data model designing

• SAS relationship concept

SESSION – 4

• SAS loops and arrays

• SAS first. And last.

• SAS functions (Character, Numeric and Datetime)

SESSION – 5

• SAS Summary report (Proc means, summary, univariate, freq, report and tabulate)

SESSION – 6

• Introduction to SAS SQL

• Retrieving data using

SESSION – 7

• SAS Introduction to Macro Facility

• Creating my first macro using parameters

• Understand the concept of macro statement, options and functions

• Creating Macro Variable using %Let, Keyword and Positional parameters, Call symput

• Macro debugging options

• Conditional macro statement

• Macro Expressions

• Macro Quoting

• Macro Functions

• Storing and using of Macros

Python Base and Advanced Programming

Python is a high-level programming language and it is mainly used in the field of mathematics and complex program designing, web development, software development and system scripting. However we will learn Python program uses for data analytics here

COURSE CURRICULUM

SESSION – 1

• Python Overview and Installation steps

• Introduction to Python Editors & IDE’s (Canopy, Pycharm, Jupyter, Rodeo, Ipython etc…)

• Work around Jupiter Notebook and its customized settings

• Importing Packages (NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc)

• Installing & loading Packages & Name Spaces

• Data Types & Data objects/structures

• Variable Types and Values

• Reading and writing data (Importing and Exporting)

SESSION – 2

• Data Manipulation Steps

SESSION – 3

• Vertical Join- Appending

• Horizontal Join- Merging

SESSION – 4

• Control flow & conditional statements

• Python Functions

SESSION – 5

• Data Analysis and Visualization steps

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Real-world Applications and Case Studies:

• Showcase success stories of individuals who underwent advanced data science training.

• Explore how these individuals applied their skills to real-world scenarios and made a significant impact.

Industry-Relevant Projects and Capstone Experiences:

• Emphasize the importance of hands-on projects and capstone experiences in advanced training.

• Discuss how these experiences prepare individuals for the complexities of the professional landscape.

Networking and Collaboration Opportunities:

• Highlight the role of networking in career growth.

• Explore how advanced data science training institutes facilitate collaboration with industry professionals and experts.

Alumni Success Stories:

• Feature stories of successful alumni who attribute their career growth to advanced data science training.

• Discuss the diverse career paths that advanced training can open up.

The Future Landscape of Data Science:

• Offer insights into emerging trends in data science and how advanced training prepares individuals for the future.

• Discuss the role of continuous learning in staying relevant in the field.

What is the fastest way to learn data science?

Steps To Learn Data Science

• Build a Strong Foundation in Statistics and Math.

• Learn Programming With Python and R.

• Get Familiar With Databases.

• Learn Analysis Methods.

• Learn, Love, Practice, and Repeat.

• Learn How To Use the Tools.

• Work on Data Science Projects.

• Become a Data Storyteller.

Does data science require advanced coding?

Does Data Science Require Coding? Yes, data science needs coding because it uses languages like Python and R to create machine-learning models and deal with large datasets.

Conclusion:

In conclusion, advanced data science training institutes play a pivotal role in shaping the next generation of data scientists. By investing in advanced education, professionals can position themselves for exciting career opportunities and contribute meaningfully to the ever-expanding world of data science. Choose the right institute, embrace continuous learning, and elevate your career beyond the basics.