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
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.
- Python can be used to develop prototypes, and quickly because it is so easy to work with and read.
- 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.
- 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.
- Python powers Django, a complete and open source web application framework. Frameworks – like Ruby on Rails – can be used to simplify the development process.
- 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/Date||9:00AM – 10:30AM||11 :OOAM – 12:30PM||2:OOPM – 3:30PM||3:45PM – 5:00PM|
|Day 1||Introduction to python and its Applications Installation of python IDE||Tea Break||Introduction and variables Built in functions||Lunch Break||Conditions Iterations||Tea Break||Functions|
|Day 2||Strings Tuples||Tea Break||Lists||Lunch Break||Regular Expression Exception Handling||Tea Break||Object Oriented Programming.|
|Day 3||Introduction to Raspberry Pi Architecture and Hardware specifications||Tea Break||Brief introduction to Linux (embedded)||Lunch Break||introduction to ARM 11 microcontroller||Tea Break||Introduction to ARM11 microcontroller|
|Day 4||Hands-on session will include Setting up Raspberry PI||Tea Break||Flashing the loading the MicroSD card with the OS Booting the OS.||Lunch Break||Intro of items on the desktop (Debian Linux) Intro and hands-on coding of Python Enabling GPIO pins LED interfacing using the GPIO||Tea Break||Physical 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/Date||9:00AM – 10:30AM||11:00AM – 12:30PM||2:00PM – 3:30PM||3:45PM – 5:00PM|
|DAY1||Introduction to Python||Tea Break||Introduction and variables|
Built in functions
|Tea Break||Lists||Lunch Break||Regular Expression|
|Tea Break||Object Oriented Programming.|
|DAY3||Introduction to Django||Tea Break||Getting Started|
Setting up a Database
|Lunch Break||The Basics of Dynamic Web||Tea Break||UI|
Module 1: HTML 5
Module 2: Java Script
Module 3: Angular JS
|DAY4||The Django Template System||Tea Break||Interacting with a Database: Models|
ØDefining Models in Python
|Lunch Break||The Django Administration Site||Tea Break||Form Processing|
Artificial Intelligence using Python
|Day/Date||9:00AM – 10:30AM||11:00AM – 12:30PM||2:00PM – 3:30PM||3:45PM – 5:00PM|
|Day 1||Introduction to python and its Applications Installation of python IDE Strings||Tea Break||Introduction and variables Built in functions Lists||Lunch Break||Conditions Iterations Regular Expression||Tea Break||Functions Object Oriented Programming|
|Day 2||Tuples||Tea Break||Lunch Break||Exception Handling||Tea Break|
|Day 3||Data manipulation||Tea Break||Introduction to NumPy, SciPy||Lunch Break||Exploratory data analytics using PANDAS||Tea Break||Introduction to Machine Learning (Supervised & Unsupervised data)|
|Day 4||Linear Algorithms||Tea Break||Clustering Techniques||Lunch Break||Decision Trees||Tea Break||Random 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 / Activities||Objectives||Outcomes||Hours|
|1||Introduction to Data Science and some use cases||This 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|
|2||Data manipulation and exploratory data analytics||Learn to juggle data using R and do EDA||1.Understand different data analysis techniques and learn to visualize the data||Theory – 30 mins|
Lab- 2.30 hours
|3||Data Import Techniques in R||This module tells you about the robustness of R in terms of importing any file formats, datasets from different sources||1.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|
|4||Deep Dive into Shiny Web App||In 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|
|5||Introduction to Machine Learning||This 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|
|6||Linear and Logistic Regression||In 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|
|7||Clustering Techniques||Learn about unsupervised learning and it’s different clustering techniques||1.Understand and implement K-means|
2.Understand and implement K medoids
3.Understand and implement K nearest and hierarchical clustering
|Lab – 3 hours|
|8||Decision Trees and Random Forest||This 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|
|9||Text Mining||To understand Text mining algorithms and sentiment analysis using it.||1.Text mining algorithms|
|11||Proof of concept project||Working on Sample dataset to demonstrate the techniques learnt throughout the workshop||1.Demonstrate ability to apply analytics and machine learning techniques||Lab – 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.
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