Data Science Virtual Internship - Part 3 (GE Data Analytics)

Data Professor · Beginner ·📊 Data Analytics & Business Intelligence ·6y ago

Key Takeaways

The video discusses the GE Data Analytics Virtual Internship, a self-paced online program that provides practical experience in data science and analytics, covering topics such as data engineering and data visualization using tools like Postgres and SQL.

Full Transcript

welcome back to the data professor YouTube channel if you new here my name is Shannon non-sena mod and I'm an associate professor of bioinformatics on this YouTube channel we cover about data science concepts and practical tutorials so if you're into this type of content please consider subscribing and so in this video I'm going to show you how you can get a virtual internship at General Electric's or GE and so this virtual internship will be a part of the GE Explorer series and it's going to be called digital technology data analytics program and so if you're enthusiastic about data science and data analytics they consider doing this virtual internship to kick-start your data science career and journey and so without further ado let's get started okay so this is the website of the GE Explorer series digital technology data analytics program I'm going to provide you the links of this website in the description of the video as also mentioned in the previous videos doing this virtual internship will allow you four major benefits so the first thing is that you can gain experience doing this data analytics program virtually and second point is that you could complete the program in only five to six hours and since the program is self-paced you can spend time whenever you're free to complete the program and the third benefit is that you're gonna gain practical experience directly from General Electric and the fourth major benefit is that you could include this experience in your CV and your LinkedIn profile and so let's begin with the details of this program so if you're keen in data science and data analytics you want to give this program a try so this GE Explorer digital technology data analytics program will allow you to learn from GE and gain insights into some of the cutting-edge project that they are working on and how you can solve and tackle real-life problems and so let's grow down further and so this is the introductory video from GE aviation CIO and you can click on the video in order to see the introductory video and in addition to the four benefits that I have talked about earlier on by completing this GE program you will also earn a certificate that you could share to your potential employers okay so let's have a look at the components of this virtual internship so what will we learn from this digital technology data analytics program and so as we can see here there are a total of two modules in this program so the first module will be data engineering and you're gonna use data engineering to combine full flight engine data part manufacturing data airport location data in order to determine the distance traveled for each airplane and some of the skills that you will acquire from this module include Postgres sequel data orchestration and transformation and critical thinking and the second module will be data visualization and so for this one you will use the data to create a run chart and a KPI which is the key performance indicators and so the second module is data visualization and according to the description you will learn about how to use data to create a run chart and KPI tables based off of simulated aviation data and some of the practical skills that you will acquire from this module includes making a run charts data storytelling through visualization and business intelligence and so upon submission of your answers you could also compare yours with the real model solutions that was created by the GE team so you could compare and contrast the answers you provide and the one provided by GE and as I mentioned before this program is totally self-paced and you can complete the program in only five to six hours and you will be able to earn a shareable certificate of this virtual internship experience which you could use for your employment application and also include it in your CV as well as your LinkedIn profile and if you find value in this video please give it a thumbs up and if you haven't yet subscribed to the channel please go ahead and subscribe and as always the best way to learn data science is to do data science and please enjoy the journey thank you for watching please like subscribe and share and I'll see you in the next one but in the meantime please check out these videos

Original Description

In this video, I will show you how you can get started on your Data Science Journey and Data Science Career by starting this Virtual Internship (Online Internship) anywhere in the world with GE Digital Technology Data Analytics Program. At the completion of your virtual internship you can showcase your accomplishment on your CV and LinkedIn. 🌟 Buy me a coffee: https://www.buymeacoffee.com/dataprofessor ⭕ Digital Technology Data Analytics Program [GE Explorer Series ] ✅https://www.insidesherpa.com/virtual-internships/prototype/ThbphD5N5WRsd9Mxo/Digital-Technology-(Data-Analytics)-Virtual-Experience-Program ⭕ Playlist: Check out our other videos in the following playlists. ✅ Data Science 101: https://bit.ly/dataprofessor-ds101 ✅ Data Science YouTuber Podcast: https://bit.ly/datascience-youtuber-podcast ✅ Data Science Virtual Internship: https://bit.ly/dataprofessor-internship ✅ Bioinformatics: http://bit.ly/dataprofessor-bioinformatics ✅ Data Science Toolbox: https://bit.ly/dataprofessor-datasciencetoolbox ✅ Streamlit (Web App in Python): https://bit.ly/dataprofessor-streamlit ✅ Shiny (Web App in R): https://bit.ly/dataprofessor-shiny ✅ Google Colab Tips and Tricks: https://bit.ly/dataprofessor-google-colab ✅ Pandas Tips and Tricks: https://bit.ly/dataprofessor-pandas ✅ Python Data Science Project: https://bit.ly/dataprofessor-python-ds ✅ R Data Science Project: https://bit.ly/dataprofessor-r-ds ⭕ Subscribe: If you're new here, it would mean the world to me if you would consider subscribing to this channel. ✅ Subscribe: https://www.youtube.com/dataprofessor?sub_confirmation=1 ⭕ Recommended Tools: Kite is a FREE AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite and I love it! ✅ Check out Kite: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from Data Professor · Data Professor · 0 of 60

← Previous Next →
1 How a Biologist became a Data Scientist
How a Biologist became a Data Scientist
Data Professor
2 WEKA Tutorial #1.1 - How to Build a Data Mining Model from Scratch
WEKA Tutorial #1.1 - How to Build a Data Mining Model from Scratch
Data Professor
3 WEKA Tutorial #1.2 - How to Build a Data Mining Model from Scratch
WEKA Tutorial #1.2 - How to Build a Data Mining Model from Scratch
Data Professor
4 WEKA Tutorial #1.3 - How to Build a Data Mining Model from Scratch
WEKA Tutorial #1.3 - How to Build a Data Mining Model from Scratch
Data Professor
5 Computational Drug Discovery: Machine Learning for Making Sense of Big Data in Drug Discovery
Computational Drug Discovery: Machine Learning for Making Sense of Big Data in Drug Discovery
Data Professor
6 Quotes #1 on Big Data and Data Science
Quotes #1 on Big Data and Data Science
Data Professor
7 Quotes #2 on Big Data and Data Science
Quotes #2 on Big Data and Data Science
Data Professor
8 Quotes #3 on Big Data and Data Science
Quotes #3 on Big Data and Data Science
Data Professor
9 Quotes #4 on Big Data and Data Science
Quotes #4 on Big Data and Data Science
Data Professor
10 Quotes #5 on Big Data and Data Science
Quotes #5 on Big Data and Data Science
Data Professor
11 Data Science 101: Starting a Data Science / Data Mining Project
Data Science 101: Starting a Data Science / Data Mining Project
Data Professor
12 Data Science 101: CRISP-DM - Data Mining / Data Science in 6 Steps
Data Science 101: CRISP-DM - Data Mining / Data Science in 6 Steps
Data Professor
13 R Programming 101: How to Define Variables
R Programming 101: How to Define Variables
Data Professor
14 R Programming 101: Read and Write CSV files
R Programming 101: Read and Write CSV files
Data Professor
15 Data Science 101: Basic Command-Line for Data Science
Data Science 101: Basic Command-Line for Data Science
Data Professor
16 Strategies for Learning Data Science in 2020 (Data Science 101)
Strategies for Learning Data Science in 2020 (Data Science 101)
Data Professor
17 Building your Data Science Portfolio with GitHub (Data Science 101)
Building your Data Science Portfolio with GitHub (Data Science 101)
Data Professor
18 R Programming 101: Setting up R programming environment (R, RStudio and RStudio.cloud)
R Programming 101: Setting up R programming environment (R, RStudio and RStudio.cloud)
Data Professor
19 Exploratory Data Analysis in R: Towards Data Understanding
Exploratory Data Analysis in R: Towards Data Understanding
Data Professor
20 Exploratory Data Analysis in R: Quick Dive into Data Visualization
Exploratory Data Analysis in R: Quick Dive into Data Visualization
Data Professor
21 Machine Learning in R: Building a Classification Model
Machine Learning in R: Building a Classification Model
Data Professor
22 Machine Learning in R: Repurpose Machine Learning Code for New Data
Machine Learning in R: Repurpose Machine Learning Code for New Data
Data Professor
23 Data Science 101: Deploying your Machine Learning Model
Data Science 101: Deploying your Machine Learning Model
Data Professor
24 Machine Learning in R: Deploy Machine Learning Model using RDS
Machine Learning in R: Deploy Machine Learning Model using RDS
Data Professor
25 Data Pre-processing in R: Handling Missing Data
Data Pre-processing in R: Handling Missing Data
Data Professor
26 Machine Learning in R: Speed up Model Building with Parallel Computing
Machine Learning in R: Speed up Model Building with Parallel Computing
Data Professor
27 Data Science 101: Overview of Machine Learning Model Building Process
Data Science 101: Overview of Machine Learning Model Building Process
Data Professor
28 Web Apps in R: Building your First Web Application in R | Shiny Tutorial Ep 1
Web Apps in R: Building your First Web Application in R | Shiny Tutorial Ep 1
Data Professor
29 Web Apps in R: Build Interactive Histogram Web Application in R | Shiny Tutorial Ep 2
Web Apps in R: Build Interactive Histogram Web Application in R | Shiny Tutorial Ep 2
Data Professor
30 Web Apps in R: Building Data-Driven Web Application in R | Shiny Tutorial Ep 3
Web Apps in R: Building Data-Driven Web Application in R | Shiny Tutorial Ep 3
Data Professor
31 Web Apps in R: Building the Machine Learning Web Application in R | Shiny Tutorial Ep 4
Web Apps in R: Building the Machine Learning Web Application in R | Shiny Tutorial Ep 4
Data Professor
32 Web Apps in R: Build BMI Calculator web application in R for health monitoring | Shiny Tutorial Ep 5
Web Apps in R: Build BMI Calculator web application in R for health monitoring | Shiny Tutorial Ep 5
Data Professor
33 Machine Learning in R: Building a Linear Regression Model
Machine Learning in R: Building a Linear Regression Model
Data Professor
34 What programming language to learn for Data Science? R versus Python
What programming language to learn for Data Science? R versus Python
Data Professor
35 How to Become a Data Scientist (Learning Path and Skill Sets Needed)
How to Become a Data Scientist (Learning Path and Skill Sets Needed)
Data Professor
36 Using Python in R
Using Python in R
Data Professor
37 Interpretable Machine Learning Models
Interpretable Machine Learning Models
Data Professor
38 Making Scatter Plots in R [Data Visualisation in R series]
Making Scatter Plots in R [Data Visualisation in R series]
Data Professor
39 Machine Learning in Python: Building a Classification Model
Machine Learning in Python: Building a Classification Model
Data Professor
40 Compare Machine Learning Classifiers in Python
Compare Machine Learning Classifiers in Python
Data Professor
41 Hyperparameter Tuning of Machine Learning Model in Python
Hyperparameter Tuning of Machine Learning Model in Python
Data Professor
42 Practical Introduction to Google Colab for Data Science
Practical Introduction to Google Colab for Data Science
Data Professor
43 File Handling in Google Colab for Data Science
File Handling in Google Colab for Data Science
Data Professor
44 Pandas for Data Science: Create and Combine DataFrames / Rename Columns
Pandas for Data Science: Create and Combine DataFrames / Rename Columns
Data Professor
45 Machine Learning in Python: Building a Linear Regression Model
Machine Learning in Python: Building a Linear Regression Model
Data Professor
46 Machine Learning in Python: Principal Component Analysis (PCA) for Handling High-Dimensional Data
Machine Learning in Python: Principal Component Analysis (PCA) for Handling High-Dimensional Data
Data Professor
47 How to Plot an ROC Curve in Python | Machine Learning in Python
How to Plot an ROC Curve in Python | Machine Learning in Python
Data Professor
48 Installing conda on Google Colab for Data Science
Installing conda on Google Colab for Data Science
Data Professor
49 Use native R on Google Colab for Data Science
Use native R on Google Colab for Data Science
Data Professor
50 How to Save and Download files from Google Colab
How to Save and Download files from Google Colab
Data Professor
51 Easy Web Scraping in Python using Pandas for Data Science
Easy Web Scraping in Python using Pandas for Data Science
Data Professor
52 Data Science for Computational Drug Discovery using Python (Part 1)
Data Science for Computational Drug Discovery using Python (Part 1)
Data Professor
53 Pandas Profiling for Data Science (Quick and Easy Exploratory Data Analysis)
Pandas Profiling for Data Science (Quick and Easy Exploratory Data Analysis)
Data Professor
54 Exploratory Data Analysis in Python using pandas
Exploratory Data Analysis in Python using pandas
Data Professor
55 Quick tour of PyCaret (a low-code machine learning library in Python)
Quick tour of PyCaret (a low-code machine learning library in Python)
Data Professor
56 How to Upload Files to Google Colab
How to Upload Files to Google Colab
Data Professor
57 How to Install and Use Pandas Profiling on Google Colab
How to Install and Use Pandas Profiling on Google Colab
Data Professor
58 How to Adjust the Style of Pandas DataFrame
How to Adjust the Style of Pandas DataFrame
Data Professor
59 How to use Bamboolib for Data Wrangling in Data Science
How to use Bamboolib for Data Wrangling in Data Science
Data Professor
60 How to use Pandas Profiling on Kaggle
How to use Pandas Profiling on Kaggle
Data Professor

The GE Data Analytics Virtual Internship is a self-paced online program that provides practical experience in data science and analytics, covering topics such as data engineering and data visualization. The program is designed to help individuals gain experience and skills in data analytics, and can be completed in 5-6 hours. Upon completion, participants will receive a shareable certificate that can be used for employment applications.

Key Takeaways
  1. Register for the GE Explorer series Digital Technology Data Analytics Program
  2. Complete the introductory video from GE Aviation CIO
  3. Finish the two modules: Data Engineering and Data Visualization
  4. Use Postgres and SQL for data engineering
  5. Create a run chart and KPI tables using simulated aviation data
  6. Compare your answers with the real model solutions provided by GE
  7. Earn a shareable certificate upon completion
💡 The program provides a unique opportunity for individuals to gain practical experience in data science and analytics, and to learn from a leading company like GE.

Related Reads

📰
I Built My First Web Scraper in Python — Here’s What Broke Immediately
Learn from a developer's first-hand experience of building a web scraper in Python and what went wrong, to improve your own web scraping skills
Medium · Data Science
📰
Building multi-Region visualizations with Highcharts in Amazon Quick
Learn to build multi-Region visualizations with Highcharts in Amazon QuickSight, overcoming native chart limitations while maintaining data sovereignty
AWS Machine Learning
📰
When Data Science Makes Us Sad: The Story of an Overbooked Flight
Learn how data science can inform business decisions, such as overbooking flights, and the potential consequences of these decisions
Towards Data Science
📰
The Loudest Stock of the Week Got 1,363 Mentions. The Best Signal Got 75.
Learn how to analyze stock mentions on social media to identify market trends and signals, and why the loudest stock of the week may not be the best signal
Medium · Data Science
Up next
Question #2: AI ke baad Data Analyst ka role khatam ho jayega? 🤖
Project Shift
Watch →