Data Expert Course with Alphaa AI

Firstly, We are blown away by the love and support you have shown for us on LinkedIn for our courses. To say we are touched would be an understatement. ?

It took us some time to get the details of the course together since it was an impromptu decision. Looking at how many of you attended our live sessions, we wanted to put it in a structure that can cater to all the questions we received. But here are we now, and will definitely improve from here. ??

Over the next few weeks, we would be conducting an exclusive #Alphaa AI Data Expert course on #LinkedInLive.

Why you should attend?

This is intended to be a Data Track "crash course" that will prepare you to

1. Learn to set up data lake, data warehouse, and databases

2. Dive into your data, using SQL and Visualisation tools

3. Get familiarised with what is data analytics, and its components,

4. Ask the right questions, work with data, and pick the right tools and specialization for advanced analytics.

When?

Every Saturday starting May 30, 2020. It's an hour-long session and we will keep it open for QnA in the last 20 mins. Links to each session will be shared in the LinkedIn events mentioned in each chapter. Please register yourself to get regular notifications.

Who should attend?

Students, Non-IT Professionals, Data Enthusiasts. Whoever is curious about Data and want to learn a few things to set up the environment and perform analytics.

Where?

We will be doing once a week One Hour Session on Saturdays. You can participate through LinkedIn Live and Youtube Live, links will be updated through Linkedin Events. You can also subscribe to our mailing list here, so we can share relevant study source and course summaries with you. (If done already, please skip)

Session Details

Week 1: Introduction to Databases, Data-warehouses & Data Lakes with major differences and similarities between them. This week, we will focus on choosing the right data storage mechanism and business use-cases. Theory + Live Demo

Attend Here: 

LinkedIn Event Link 

Week 2: Data Visualisation-MS Excel / Alphaa / Tableau. Now that your data has been stored in a data warehouse or data lake, it’s time to start the visualization journey. We will focus on the current market tools and choosing the right approach based on your data strategy. 

Theory + Live Demo. 

Attend Here: 

LinkedIn Event Link 

Week 3: Cleaning + Creating Data - Writing SQL. In this week, we will focus on a very important part of any Data Strategy. We will focus on:

• Data quality
• Data profiling
• Data prep
• Data transformation and assurance
• Data quality impact on AI and Machine Learning
• Writing SQL (General and Complex Queries Rules)
• Tables and Joins

Theory + Live Demo. 

Attend Here: 

LinkedIn Event Link 

Week 4: Doing Forecasting - AWS Forecast

In the final chapter, we will focus on predictive analytics using popular online AI/ML services (Such as AWS). The session will focus on creating easy forecast models for business use-cases. 

Theory + Live Demo. 

Attend Here: 

LinkedIn Event Link

Certification Test: We will share with you a questionnaire and a project to gauge your learning and post-submission of that you will be awarded an Alphaa AI Data Expert Certification. No cost attached. 

Sessions will also be available post Live on our Youtube Channel, and we will shortly open up Forum for all your questions and discussions. Please confirm your participation in them so that you don’t miss out on any updates. Thank you and Stay Safe! 

Alphaa AI - Creating the next billion Citizen data scientists.

Note: 

1. We hope you understand that we are a young focused team with limited resources and we are trying to do our best to get this course out so that you can get a view of what the fuss is about. :)
2. There are many courses available online and if you can you should enroll in them to get deep expertise. Here we are trying to provide a perspective for students, non-IT professionals, and data enthusiasts and whoever wants to get started in Data Science. 
3. We will be inclined to do more detailed sessions depending upon how the response is and add community managers to help us with this initiative.
4. If you feel we can add a few things to make the experience and learning better please let us know, we definitely want to improve.