Update assignment2.md

assignments/assignment2.md

-# Assignment 2
 
 
+# Assignment 1
 
+Hey there! Welcome to Knowledge Lens Intern Training Program.
 
-## Task 1: Working with Mongo - Advanced
+This Assignment will serve as a quick refresher on the usage of NoSQL and Time-series databases.
+There are three tasks in this assignment, on completion of which you'll learn:
+*  How to interact with Mongo DB
+*  Using Pandas Dataframe and generating your own excel reports
+*  Leveraging Kairos Time-series database for data ingestion and querying the same
+*  Publishing and Consuming messages via MQTT protocol
+*  Caching mechanism using Redis DB 
 
+Happy Coding! :tada:
 
-## Areas covered:
+## :pushpin: Task 1: Working with Mongo - Advanced
+
+
+### :golf: Areas covered:
 - Timeseries Operation
 - Working with NoSQL
 - Working with Pandas
 
-## Description:
-You are given with a dataset of bicycle rental company in the form of a JSON file. The end goal of the project is to create an API interface that will provide the following: 
+### :books: Description:
 
+You are given with a dataset of bicycle rental company in the form of a JSON file. The end goal of the project is to create an API interface that will provide the following: 
 1.  Get the user who has the highest trip duration.
 2. Get the user who has used the service the most.
 3. Generate Excel Report based on `bike id`, `station name` and `start date`
-
 Sample Document:
 ```json
 {
@@ -51,33 +61,34 @@ Sample Document:
  }
 }
 ```
-
 Bonus Points: Use Mongo Aggregate framework
 
-### Tools to use: 
+### :wrench: Tools to use: 
 1. Pycharm / VSCode
 2. Robo3T / Studio3T / MongoDB Compass
 3. PyMongo
 
 
-### Reference:
-https://www.mongodb.com/docs/manual/tutorial/query-documents/
-https://www.mongodb.com/docs/manual/reference/operator/aggregation-pipeline/
-https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_excel.html
-https://fastapi.tiangolo.com/advanced/custom-response/#fileresponse
-https://pymongo.readthedocs.io/en/stable/
+### :mag: References:
+* [Querying Documents on Mongo](https://www.mongodb.com/docs/manual/tutorial/query-documents/)
+* [Quick Summary on Mongo Aggregation Stages](https://www.mongodb.com/docs/manual/reference/operator/aggregation-pipeline/)
+* [Generating Excel Sheets from a Pandas Dataframe](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_excel.html)
+* [How to return files on FastAPI response](https://fastapi.tiangolo.com/advanced/custom-response/#fileresponse)
+* [PyMongo Official Documentation](https://pymongo.readthedocs.io/en/stable/)
+
 
 
-________________________________________________________
-## Task 2: Working with Timeseries
+_________________________________
 
+## :pushpin: Task 2: Working with Timeseries
 
-## Areas covered:
+
+### :golf: Areas covered:
 - Timeseries Operation
 - Working with Timeseries
 - Working with Pandas
 
-## Description:
+### :books: Description:
 You are given with a dataset of weather in the form of a CSV file. The end goal of the project is to create an API interface that will provide the following: 
 
 1. Get daily, monthly, weekly and monthly aggregate (min, max, and average) of the data and generate report in Excel format.
@@ -90,17 +101,25 @@ Sample Document:
 |2006-04-01 00:00:00.000 +0200|Partly Cloudy|rain       |9.472222222    |7.388888889             |0.89    |14.1197          |251                   |15.8263        |0         |1015.13             |
 
 
-### Tools to use: 
+### :wrench: Tools to use: 
 1. Pycharm / VSCode
 2. Pandas 
+3. Kairos
+
+### :mag: References:
+* [How to query Kairos DB using Metrics](https://kairosdb.github.io/docs/restapi/QueryMetrics.html)
+
 
-### Reference:
-https://kairosdb.github.io/docs/restapi/QueryMetrics.html
-https://pypi.org/project/kairosdb-python/
+------------------------------------------------------
 
-## Task 3: Working with MQTT & REDIS
+## :pushpin: Task 3: Working with MQTT & REDIS
+
+### :golf: Areas covered:
+- MQTT Protocol
+- Caching using Redis DB
+
+### :books: Description
 
-# Description
 
 In a theatre, Tickets are to be given to people in queue, There are 2 counters for Gold  and Silver class.
 
@@ -111,7 +130,7 @@ Store the information of booking, Maximum 5 tickets allowed in a booking.
 
 - Publish message to a MQTT topic
 
-- Subscribe message, Assign seats per requirement and store information to redis db.
+- Subscribe message, Assign seats per requirement and store information to Redis db.
 
 sample format: 
 ```json
@@ -122,17 +141,18 @@ sample format:
 	}
 ```
 	   
-Use Redis for caching/storing information
+Use Redis for caching/storing information.
 
-create consumer's which consumes data from these topics and store to a redis db
+Create consumer's which consumes data from these topics and store to a Redis db.
 
-### Tools to use: 
+### :wrench: Tools to use: 
 1. Pycharm / VSCode
-2. MQTT - (paho-mqtt)
-3. REDIS - (redis)
+2. MQTT - (PIP package: `paho-mqtt`)
+3. REDIS - (PIP package: `redis`)
+
+### :mag: References:
+* [Using MQTT in Python](https://www.emqx.com/en/blog/how-to-use-mqtt-in-python)
+* [Connection to Redis in Python](https://docs.redis.com/latest/rs/references/client_references/client_python/)
 
-### Reference:
-https://www.emqx.com/en/blog/how-to-use-mqtt-in-python
 
-https://docs.redis.com/latest/rs/references/client_references/client_python/