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From Garage to GooglePles. Larry Page & Sergy Brin

From Garage to GooglePles. Larry Page & Sergy Brin

Message for Students

Elun Musk what he says?

I don't give damn about your college Degree. Don't waste time in college degree 

Acquiring the appropriate technical skills is a crucial factor in achieving success. Many successful individuals, such as Bill Gates, Steve Jobs, and Larry Ellison, are college dropouts. Our education system is more of a formality, sluggish, expensive and outdated. It is not making youth industry ready. Check the FAQs below.

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FAQs from students

01

Can anyone shift to IT field? Yes, regardless of engineering background. Challenges include competition due to high demand. Success requires high IQ, hard work, and dedication. Contact me for further information.

02

What about my academics? 

To succeed in your job search, identify companies that prioritize technical skills. With persistence and dedication, prepare to excel in interviews and demonstrate your ability to drive business growth.

03

Is the data science stream easier than other IT fields?

"Data science app development requires diverse skills. Learning programming to a certain depth is beneficial for job opportunities."

04

Can you get job placement?"

To excel in your job search, target companies valuing technical skills. Prepare thoroughly and showcase your ability to drive business growth in interviews.

05

Can I do self-learning?

"Yes. A Mentor with his experience can provide significant value. Be mindful to evaluate and choose the right mentor."

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06

Will you give notes?

No. We do not believe in legacy outdated training methods, inclucated in mind of students. We can offer you references, guidance, dynamic learning techniques, real-time project assignments that will enable you to install and work on software.

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Sphere on Spiral Stairs
"Start your foot step with C, The mother of all programming language "
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Curriculam Overview

Phase 1: 

DBMS, RDBMS, ER & Dimension Modelling, SQL programming

Project

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Phase 2: 

Programming:

Comparitive learning basics with C, OOPs with C++ and Advanced concepts with Java

Python programming

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​Descriptive statistics & Exploratory Data Analytics. Data Visualization

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Inferential statistics

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Regression & Tree and Classification models.

Feature Engineering

SVM 

Handling unlabed data with clustering models.

Miscellanious concepts

NLP - Textual Analytics

Sentimental Analysis

Artificial Neural Network

Image & sound processing

 

Tensorflow Tutorial

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Big Data

Concepts of Hadoop Framework

Different Componets of Hadoop

Hive & Pig

Knowledge Aquisition

Knowledge Presentation

Knowledge Management

 

Profile building

Profile marketting

 

Mock interviews at various levels

Certificate

Letter of experience of internship

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Envision your learning strategy
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