Industry Institution Participation Program

Big Data, Analytics, Machine learning and Deep learning techniques are the most sought-after technologies of 21st centuries and the demand is growing exponentially. Recently we see that there is a huge gap between the resources produced by engineering colleges and the skill set Industry is expecting. According to a survey, out of 20 lacks students coming out of engineering colleges every year only about 180,000 students are getting hired!
Keeping this in mind, we strive to bridge this gap by Introducing Industry and Institution Participation Program.

What is IIPC?
It’s a program to bring colleges and Industries together to a single platform to understand what Industry is expecting in terms of skillset and then training students accordingly.

Our Training Programs
GoLearn conducts workshop in colleges on technologies like Python & Django for web programming, Python for Machine learning using Numpy, Scipy, Pandas, Sci-kit learn, deep learning using Keras, Tensorflow, Artificial Neural Networks, Deep neural networks, Recurrent Neural Networks, Data Science using R etc. to produce job-ready students from Colleges.


Here is a detailed list of workshop we conduct for Colleges,

IOT using Python, Raspberry Pi & Django Web Programming using Python & Django Artificial Intelligence using Python Data Science using R

IOT using Python, Raspberry Pi & Django

Internet of Things (IoT) has been the hottest topic amongst hardware developers for past few years. Open source hardware like Raspberry Pi along with open source language like Python enables anybody to frame IoT devices. Innovation in all fields of technology can derive benefits from this combination. Present workshop is aimed to impart knowledge about using Raspberry Pi and python to make simple devices where signals from sensors can be derived to control electronic devices and/or to make decisions. With this basic introduction about IoT fabrication, an audience can innovate in their domain and come up with uniquely innovative solutions to real-world problems.

Python is a language that is remarkably easy to learn, and it can be used as a stepping stone into other programming languages and frameworks. If you’re an absolute beginner and this is your first time working with any type of coding language, that’s something you definitely want.

Python is widely used, including by a number of big companies like Google, Pinterest, Instagram, Disney, Yahoo!, Nokia, IBM, and many others. The Raspberry Pi – which is a mini computer and DIY lover’s dream – relies on Python as its main programming language too. You’re probably wondering why either of these things matters, and that’s because once you learn Python, you’ll never have a shortage of ways to utilize the skill. Not to mention, since a lot of big companies rely on the language, you can have good job market as a Python developer.

  1. Python can be used to develop prototypes, and quickly because it is so easy to work with and read.
  2. Most automation, data mining, and big data platforms rely on Python. This is because it is the ideal language to work with for general purpose tasks.
  3. Python is easy to read, even if you’re not a skilled programmer. Anyone can begin working with the language, all it takes is a bit of patience and a lot of practice. Plus, this makes it an ideal candidate for use among multi-programmer and large development teams.
  4. Python powers Django, a complete and open source web application framework. Frameworks – like Ruby on Rails – can be used to simplify the development process.
  5. It has a massive support base thanks to the fact that it is open source and community developed. Millions of like-minded developers work with the language on a daily basis and continue to improve core functionality. The latest version of Python continues to receive enhancements and updates as time progresses. This is a great way to network with other developers.

PYTHON IS A HOT COMMODITY IN THE ERA OF INTERNET OF THINGS (IOT)

The advent of the Internet of Things introduces countless opportunities for Python programmers.

Platforms like Raspberry Pi, a series of credit card-sized computers running Python, allow developers to build their own exciting devices like cameras, radios, phones, and even games through Python with ease.

With advanced Python programming concepts, developers can homebrew their own gadgets, and connect them with real-world markets independently and on the cheap.

TECH GIANTS LOVE PYTHON. TECH IT GIANTS LOVE PYTHON.

This workshop will introduce you to the unexplored potential of the Raspberry Pi-the hardware, software and its applications. The Workshop is designed to cater to all kinds – be it a novice or a tech-savvy hobbyist or an expert developer extraordinaire.
During the course of the workshop interesting open problems are floated and the participants are encouraged to think out-of-box and come up with innovative solutions. Post workshop, each participant will have a sound exposure to Python programming and interfacing of Raspberry Pi 3.

A perfect recipe for innovation!

The WorkShop Outlines the following Concepts

Day/Date9:00AM – 10:30AM 11 :OOAM – 12:30PM 2:OOPM – 3:30PM 3:45PM – 5:00PM
Day 1Introduction to python and its Applications Installation of python IDETea BreakIntroduction and variables Built in functionsLunch BreakConditions IterationsTea BreakFunctions
Day 2Strings TuplesTea BreakListsLunch BreakRegular Expression Exception HandlingTea BreakObject Oriented Programming.
Day 3Introduction to Raspberry Pi Architecture and Hardware specificationsTea BreakBrief introduction to Linux (embedded)Lunch Breakintroduction to ARM 11 microcontrollerTea BreakIntroduction to ARM11 microcontroller
Day 4Hands-on session will include Setting up Raspberry PITea BreakFlashing the loading the MicroSD card with the OS Booting the OS.Lunch BreakIntro of items on the desktop (Debian Linux) Intro and hands-on coding of Python Enabling GPIO pins LED interfacing using the GPIOTea BreakPhysical Email notifier Using HDMI port, USB ports (mouse/keyboard). Audio jack Button input and LDR interfacing Buzzer, PIR and various sensor interfacing Hands on Experience on specified applications

Web Programming using Python & Django

The workshop will help the participants understand the fundamentals of Web-Development with Python/Django well enough that they are ready to build any app they want using resources on the web. We want to do this using an innovative “Flipped classroom” methodology which teachers & students around the world have found very effective.

The workshop will teach Web Development by building a real app (choice of an e-commerce website/a daily deal website/an aggregator) using Python/Django. Web development needs a vast set of skills, including databases, frontend, backend and dev. tools, and it is hard to teach it effectively in 3 hours. We could focus on one part, say the Django framework, but the workshop becomes inaccessible for people who don’t have knowledge of all the other prerequisites.

The goal is to spend more time doing and problem-solving, rather than lecturing. Think of it as a lab session as opposed to a lecture.

1) Python can be used to develop prototypes, and quickly because it is so easy to work with and read.

2) Most automation, data mining, and big data platforms rely on Python. This is because it is the ideal language to work with for general purpose tasks.

3) Python is easy to read, even if you’re not a skilled programmer. Anyone can begin working with the language, all it takes is a bit of patience and a lot of practice. Plus, this makes it an ideal candidate for use among multi-programmer and large development teams.

4) Python powers Django, a complete and open source web application framework. Frameworks – like Ruby on Rails – can be used to simplify the development process.

5) It has a massive support base thanks to the fact that it is open source and community developed. Millions of like-minded developers work with the language on a daily basis and continue to improve core functionality. The latest version of Python continues to receive enhancements and updates as time progresses. This is a great way to network with other developers.

The current state of Python is active. Very ACTIVE. It’s being used in data sciences and web programming. It’s used in academics and is a great first language for beginners. Pen testers use it and it’s one of the BEST scripting languages.

Now Django on the other hand is not doing so well. I mean sure there are a lot of websites running on Django but Rails still continues to dominate the Web Industry alongside PHP. But Django is useful too because it’ll teach you the concepts of Python based Web Programming.

So the future currently looks good for “general purpose” web development in Python but not so much for Django.

With advanced Python programming concepts, developers can homebrew their own gadgets, and connect them with real world markets independently and on the cheap. TECH GIANTS LOVE PYTHON.

WEB GIANTS LOVE PYTHON & DJANGO.

Day/Date9:00AM – 10:30AM 11:00AM – 12:30PM 2:00PM – 3:30PM 3:45PM – 5:00PM
DAY1Introduction to PythonTea BreakIntroduction and variables
Built in functions
Lunch BreakConditions
Iterations
Tea BreakFunctions
DAY2Strings
Tuples
Tea BreakListsLunch BreakRegular Expression
Exception Handling
Tea BreakObject Oriented Programming.
DAY3Introduction to DjangoTea BreakGetting Started
Installing Django
Setting up a Database
Lunch BreakThe Basics of Dynamic WebTea BreakUI
Module 1: HTML 5
Module 2: Java Script
Module 3: Angular JS
DAY4The Django Template SystemTea BreakInteracting with a Database: Models
ØDefining Models in Python
Lunch BreakThe Django Administration SiteTea BreakForm Processing

Artificial Intelligence using Python

What is Python? Python is simple yet powerful and easy to learn the language. It is an object-oriented, high-level programming language. It is also a free and open source. Python offers a clean syntax, dynamic and its interpreted nature made it to be used in wide variety of applications today. Python offers extensive libraries to work on some of the niche and most upcoming & trending technologies like IOT, Deep Learning, Machine learning & Artificial intelligence
What is Machine Learning? Machine learning is an ability to build and train the algorithms to make machines to work as a human. Machine learning is the most talked about subject in the 21st century’s IT world. Today python is becoming the most preferred platform to learn and apply machine learning and deep learning skills which are necessary to build applications with artificial intelligence. What is Deep Learning? Deep learning is a class or a broader version of machine learning. It is a technique to learning tasks of Artificial Neural Networks (ANN) that has many layers. Some representations are loosely based on interpretation of information processing and communication patterns in a biological nervous system, such as neural coding that attempts to define a relationship between various stimuli and associated neuronal responses in the brain. It is emerging as a game changer for the data science industry!
Concepts and tools covered We would be using Python command line interface, Jupyter and Spyder IDE’s, Tensorflow and Keras libraries. Python, Numpy, Scipy, Pandas, Scikit learn, supervised and unsupervised machine learning algorithms, deep learning using Tensor Flow, Keras, Neural network algorithms. Methodology The Course content is handcrafted by Experts and it comprises of Presentation slides, Quizzes and Assignments for each Module, Class recording can be accessed in LMS. We would be using a lot of Industry specific use cases to make the learner job ready.
Day/Date9:00AM – 10:30AM 11:00AM – 12:30PM 2:00PM – 3:30PM 3:45PM – 5:00PM
Day 1Introduction to python and its Applications Installation of python IDE StringsTea BreakIntroduction and variables Built in functions ListsLunch BreakConditions Iterations Regular ExpressionTea BreakFunctions Object Oriented Programming
Day 2TuplesTea Break Lunch BreakException HandlingTea Break 
Day 3Data manipulationTea BreakIntroduction to NumPy, SciPyLunch BreakExploratory data analytics using PANDASTea BreakIntroduction to Machine Learning (Supervised & Unsupervised data)
Day 4Linear AlgorithmsTea BreakClustering TechniquesLunch BreakDecision TreesTea BreakRandom Forest

Data Science using R

R is an open source software environment and Big Data Analytics using R is the new revolution in the world of Data Analytics, being in high demand throughout Consulting industry. R is preferred by everyone because of being open source; however, there is currently a huge dearth of supply of resources in the industry with R skills coupled with Data Analytics. The average salary of Big Data Analytics with R resources is INR 18-20 lac per annum in Indian consulting industry.

Objectives of the Course
After completing the course, you will be able to understand:
• Big Data concepts, characteristics, use cases and significance of R in Big Data Analytics.
• Advanced Analytics, Data Mining, and Data Visualization tools
Key Features of the Course
• 20 hours of Live Instructor-Led Classroom sessions
• Get trained by industry expert with more than 8 years of experience
• 10 hours of real life industry project experience
• Hands-on experience in data manipulation, statistical analysis, and graphics applications
• Get completion certificate in R Programming
Who should take this course?
• This course is ideal for engineers, consultants, business analysts, scientists and researchers.


 

PROGRAMME TITLE: Data Science

No.Content / ActivitiesObjectivesOutcomesHours
1Introduction to Data Science and some use casesThis module lets you know about how Data Science is a wider perspective of Business Analytics.1.Understand what is Data Science
2.Understand how Data science is applied in different domains
3.Understand some use cases
Theory- 3 hours
2Data manipulation and exploratory data analyticsLearn to juggle data using R and do EDA1.Understand different data analysis techniques and learn to visualize the dataTheory – 30 mins
Lab- 2.30 hours
3Data Import Techniques in RThis module tells you about the robustness of R in terms of importing any file formats, datasets from different sources1.Creating Data frames
2.Importing datasets from different databases and local drives
3.Uploading CSV, TSV, Excel, Json files and delimited files to R
Lab- 2 hours
4Deep Dive into Shiny Web AppIn this module, you will learn to build web applications and dashboards using Shiny App.1.Understand Shiny web application
2.Build a shiny based web app
3.Learn to build dashboards in shiny and host it in web
Lab- 2 hours
5Introduction to Machine LearningThis module lets you know about the various Machine Learning algorithms. The two Machine Learning types are Supervised Learning and Unsupervised Learning and the difference between the two types.1.Understand difference between supervised and unsupervised learning
2.Learn about different clustering, classification techniques
Theory- 2 hours
6Linear and Logistic RegressionIn this module we will learn ‘Regression Techniques’. Linear and logistic regression is explained from the very basics with the examples and it is implemented in R using two case studies dedicated to each type of Regression discussed.1.Understand difference between Linear and Logistic regression
2.Implement regression techniques on two different datasets
Lab- 2 hours
7Clustering TechniquesLearn about unsupervised learning and it’s different clustering techniques1.Understand and implement K-means
2.Understand and implement K medoids
3.Understand and implement K nearest and hierarchical clustering
Lab – 3 hours
8Decision Trees and Random ForestThis module covers the concepts of Decision Trees and Random Forest. The Algorithm for creation of trees and forests is discussed in a step wise approach and explained with examples. At the end of the class, these are the concepts implemented on a real-life data set. The case studies are present in the LMS.1.Learn about decision trees
2.Implement decision tree and random forest on a dataset and then visualize the data
Lab- 3 hours
9Text MiningTo understand Text mining algorithms and sentiment analysis using it.1.Text mining algorithms
2.TF-IDF
2 hours
11Proof of concept projectWorking on Sample dataset to demonstrate the techniques learnt throughout the workshop1.Demonstrate ability to apply analytics and machine learning techniquesLab – 2 hours

Our course content is handcrafted by Subject Matter Experts with rich expertise in relevant technologies. These training programs are hands-on oriented with a lot of Industry specific use cases to produce job-ready resources.

Talk to us for customised content and training

Or please email us on reachus@golearnanalytics.com

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