diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000..06e1be7
Binary files /dev/null and b/.DS_Store differ
diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000..26d3352
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml
diff --git a/.idea/cloud-computing-predict.iml b/.idea/cloud-computing-predict.iml
new file mode 100644
index 0000000..d0876a7
--- /dev/null
+++ b/.idea/cloud-computing-predict.iml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>
\ No newline at end of file
diff --git a/.idea/csv-plugin.xml b/.idea/csv-plugin.xml
new file mode 100644
index 0000000..39c0600
--- /dev/null
+++ b/.idea/csv-plugin.xml
@@ -0,0 +1,16 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="CsvFileAttributes">
+    <option name="attributeMap">
+      <map>
+        <entry key="/student_solution_files/predict_detail_submission_template.csv">
+          <value>
+            <Attribute>
+              <option name="separator" value="," />
+            </Attribute>
+          </value>
+        </entry>
+      </map>
+    </option>
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000..105ce2d
--- /dev/null
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 0000000..d56657a
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9" project-jdk-type="Python SDK" />
+</project>
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 0000000..c5e8517
--- /dev/null
+++ b/.idea/modules.xml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/cloud-computing-predict.iml" filepath="$PROJECT_DIR$/.idea/cloud-computing-predict.iml" />
+    </modules>
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..50793d9
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/cloud-computing-predict" vcs="Git" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/assets/img/me.jpg b/assets/img/me.jpg
new file mode 100644
index 0000000..bbf3305
Binary files /dev/null and b/assets/img/me.jpg differ
diff --git a/assets/img/portfolio/BI.jpeg b/assets/img/portfolio/BI.jpeg
new file mode 100644
index 0000000..f619f79
Binary files /dev/null and b/assets/img/portfolio/BI.jpeg differ
diff --git a/assets/img/portfolio/BI2.jpeg b/assets/img/portfolio/BI2.jpeg
new file mode 100644
index 0000000..c5c48c5
Binary files /dev/null and b/assets/img/portfolio/BI2.jpeg differ
diff --git a/assets/img/portfolio/data-warehouse-business-intelligenc-260nw-275396558.jpeg b/assets/img/portfolio/data-warehouse-business-intelligenc-260nw-275396558.jpeg
new file mode 100644
index 0000000..fab1033
Binary files /dev/null and b/assets/img/portfolio/data-warehouse-business-intelligenc-260nw-275396558.jpeg differ
diff --git a/assets/img/portfolio/data-warehousing.jpeg b/assets/img/portfolio/data-warehousing.jpeg
new file mode 100644
index 0000000..eb62241
Binary files /dev/null and b/assets/img/portfolio/data-warehousing.jpeg differ
diff --git a/assets/img/portfolio/dataengin.jpeg b/assets/img/portfolio/dataengin.jpeg
new file mode 100644
index 0000000..518d32b
Binary files /dev/null and b/assets/img/portfolio/dataengin.jpeg differ
diff --git a/assets/img/portfolio/datawarehouse.jpeg b/assets/img/portfolio/datawarehouse.jpeg
new file mode 100644
index 0000000..0265ced
Binary files /dev/null and b/assets/img/portfolio/datawarehouse.jpeg differ
diff --git a/assets/img/portfolio/pipeline.jpeg b/assets/img/portfolio/pipeline.jpeg
new file mode 100644
index 0000000..fad8fe8
Binary files /dev/null and b/assets/img/portfolio/pipeline.jpeg differ
diff --git a/assets/mail/contact_me.js b/assets/mail/contact_me.js
index 9273d67..16d335c 100644
--- a/assets/mail/contact_me.js
+++ b/assets/mail/contact_me.js
@@ -24,7 +24,7 @@ $(function () {
             var json = {name: name, phone: phone, email: email, message: message}
             $.ajax({
                 // --- CHANGE THIS LINE TO YOUR OWN API GATEWAY  -------- 
-                url: "{Insert your own AWS API Gateway Endpoint URL here}",
+                url: "https://98005irfla.execute-api.eu-west-1.amazonaws.com/rootfunction",
                 // ------------------------------------------------------  
                 type: "POST",
                 data: JSON.stringify(json),
diff --git a/index.html b/index.html
index d6bb6d6..8b67daa 100644
--- a/index.html
+++ b/index.html
@@ -8,7 +8,7 @@
         <! --The html code below is used to set the text on the web page tab -->
         <! --You can set this to whatever you want -->
         <! --For example: {Your name - Portfolio Type} -->
-        <title>Explore Data Science Academy - Serverless Student Portfolio Web page</title>
+        <title>Thulasizwe Ntsele - Serverless Student Portfolio Web page</title>
         <!-- Favicon-->
         <link rel="icon" type="image/x-icon" href="assets/img/Untitled.ico" />
         <!-- Font Awesome icons (free version)-->
@@ -41,12 +41,12 @@
         <header class="masthead bg-primary text-white text-center">
             <div class="container d-flex align-items-center flex-column">
                 <!-- Masthead Avatar Image-->
-                <img class="masthead-avatar mb-5" src="assets/img/avataaars.svg"  alt="" />
+                <img class="masthead-avatar mb-5" src="assets/img/me.jpg"  alt="" />
                 <!-- Masthead Heading-->
                 <!-- ========= CUSTOMISE SECTION =========== -->
                 <!-- You can change 'Cloud Computing Predict' to 'Your Name' -->
                 <!-- The Masthead will then read: '{Your Name} - Project Portfolio' -->
-                <h1 class="masthead-heading text-uppercase mb-0">Cloud Computing Predict - Project Portfolio</h1>
+                <h1 class="masthead-heading text-uppercase mb-0">Thulasizwe Ntsele Cloud Computing - Project Portfolio</h1>
                 <!-- ======================================= -->
                 <!-- Icon Divider-->
                 <div class="divider-custom divider-light">
@@ -57,7 +57,7 @@ <h1 class="masthead-heading text-uppercase mb-0">Cloud Computing Predict - Proje
                 <!-- Masthead Subheading-->
                 <!-- ========= CUSTOMISE SECTION =========== -->
                 <!-- Change this to a list of three or four of your most relevant skills-->
-                <p class="masthead-subheading font-weight-light mb-0">Machine Learning - Time Series - Dashboarding</p>
+                <p class="masthead-subheading font-weight-light mb-0">Data Warehouse - Data Engineering - Business Intelligence - Predictive Models</p>
                 <!-- ======================================= -->
             </div>
         </header>
@@ -82,7 +82,7 @@ <h2 class="page-section-heading text-center text-uppercase text-secondary mb-0">
                             </div>
                             <!-- ========= CUSTOMISE SECTION =========== -->
                             <!-- Replace the link in the `src` string below to depict an image related to a project of yours -->
-                            <img class="img-fluid" src="assets/img/portfolio/christopher-robin-ebbinghaus-pgSkeh0yl8o-unsplash.jpg" alt="" />
+                            <img class="img-fluid" src="assets/img/portfolio/datawarehouse.jpeg" alt="" />
                             <!-- ======================================= -->
                         </div>
                     </div>
@@ -240,9 +240,9 @@ <h2 class="page-section-heading text-center text-uppercase text-secondary mb-0">
                     <div class="col-lg-4 mb-5 mb-lg-0">
                         <h4 class="text-uppercase mb-4">Location</h4>
                         <p class="lead mb-0">
-                            12th Floor, Rennie House, 19 Ameshoff St
+                            3A Violet Close
                             <br />
-                            Johannesburg, 2001
+                            Cape Town, 7441
                         </p>
                     </div>
                     <!-- ======================================= -->
@@ -261,9 +261,9 @@ <h4 class="text-uppercase mb-4">Around the Web</h4>
                     <!-- ========= CUSTOMISE SECTION =========== -->
                     <!-- You may wish to modify this text to align with your personal portfolio website -->
                     <div class="col-lg-4">
-                        <h4 class="text-uppercase mb-4">Explore AI Cloud Computing Predict</h4>
+                        <h4 class="text-uppercase mb-4">Thulasizwe AI Cloud Computing Project</h4>
                         <p class="lead mb-0">
-                            Create your own data science portfolio with an intelligent NPL bot handling enquiries for you.</a>
+                            Data is the future off all organisation therefore it must be treated with respect.</a>
                         </p>
                     </div>
                     <!-- ======================================= -->
@@ -294,7 +294,7 @@ <h4 class="text-uppercase mb-4">Explore AI Cloud Computing Predict</h4>
                                 <div class="col-lg-8">
                                     <!-- Portfolio Piece - Title-->
                                     <!-- Modify the title of the first portfolio project here -->
-                                    <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfolioModal1Label">Credit Fraud Detector</h2>
+                                    <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfolioModal1Label">Data Warehouse</h2>
                                     <!-- Icon Divider-->
                                     <div class="divider-custom">
                                         <div class="divider-custom-line"></div>
@@ -303,10 +303,10 @@ <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfol
                                     </div>
                                     <!-- Portfolio Piece - Image-->
                                     <!-- Modify the image of the first portfolio project here-->
-                                    <img class="img-fluid rounded mb-5" src="assets/img/portfolio/ales-nesetril-ex_p4AaBxbs-unsplash.jpg" alt="" />
+                                    <img class="img-fluid rounded mb-5" src="assets/img/portfolio/data-warehousing.jpeg" alt="" />
                                     <!-- Portfolio Piece - Text-->
                                     <!-- Modify the description of the first portfolio project here-->
-                                    <p class="mb-5">Built a credit card fraud detection system for one of South Africas big four banks</p>
+                                    <p class="mb-5">Build an electronic method of organizing, analyzing, and reporting information</p>
                                     <button class="btn btn-primary" data-dismiss="modal">
                                         <i class="fas fa-times fa-fw"></i>
                                         Close Window
@@ -335,7 +335,7 @@ <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfol
                                 <div class="col-lg-8">
                                     <!-- Portfolio Piece - Title-->
                                     <!-- Modify the title of the second portfolio project here -->
-                                    <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfolioModal2Label">Rock Formation Classifier</h2>
+                                    <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfolioModal2Label">DATA ENGINEERING</h2>
                                     <!-- Icon Divider-->
                                     <div class="divider-custom">
                                         <div class="divider-custom-line"></div>
@@ -344,10 +344,10 @@ <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfol
                                     </div>
                                     <!-- Portfolio Piece - Image-->
                                     <!-- Modify the image of the second portfolio project here-->
-                                    <img class="img-fluid rounded mb-5" src="assets/img/portfolio/sebastian-pichler-oqFHLfLFtmc-unsplash.jpg" alt="" />
+                                    <img class="img-fluid rounded mb-5" src="assets/img/portfolio/pipeline..jpeg" alt="" />
                                     <!-- Portfolio Piece - Text-->
                                     <!-- Modify the description of the second portfolio project here-->
-                                    <p class="mb-5">Designed and built a PoC rock formation density classifier to aid engineers in the preliminary building design phase</p>
+                                    <p class="mb-5">A data pipeline is a set of actions that ingest raw data from disparate sources and move the data to a destination for storage and analysis. A pipeline also may include filtering and features that provide resiliency against failure</p>
                                     <button class="btn btn-primary" data-dismiss="modal">
                                         <i class="fas fa-times fa-fw"></i>
                                         Close Window
@@ -376,7 +376,7 @@ <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfol
                                 <div class="col-lg-8">
                                     <!-- Portfolio Piece - Title-->
                                     <!-- Modify the title of the third portfolio project here -->
-                                    <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfolioModal3Label">Search for Dark Matter Hints with Machine Learning</h2>
+                                    <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfolioModal3Label">Business Intelligence</h2>
                                     <!-- Icon Divider-->
                                     <div class="divider-custom">
                                         <div class="divider-custom-line"></div>
@@ -385,10 +385,10 @@ <h2 class="portfolio-modal-title text-secondary text-uppercase mb-0" id="portfol
                                     </div>
                                     <!-- Portfolio Piece - Image-->
                                     <!-- Modify the image of the third portfolio project here -->
-                                    <img class="img-fluid rounded mb-5" src="assets/img/portfolio/halgatewood-com-OgvqXGL7XO4-unsplash.jpg" alt="" />
+                                    <img class="img-fluid rounded mb-5" src="assets/img/portfolio/BI.jpeg" alt="" />
                                     <!-- Portfolio Piece - Text-->
                                     <!-- Modify the description of the third portfolio project here-->
-                                    <p class="mb-5">This project covers several cases of detector design optimization in high energy physics experiments using Bayesian optimization with Gaussian processes</p>
+                                    <p class="mb-5">Business intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.</p>
                                     <button class="btn btn-primary" data-dismiss="modal">
                                         <i class="fas fa-times fa-fw"></i>
                                         Close Window
diff --git a/student_solution_files/DB.py b/student_solution_files/DB.py
new file mode 100644
index 0000000..c31c9ba
--- /dev/null
+++ b/student_solution_files/DB.py
@@ -0,0 +1,176 @@
+
+"""
+    Lambda function that decodes and writes data from your portfolio website to your DynamoDB database.
+
+    Author: Explore Data Science Academy.
+
+    Note:
+    ---------------------------------------------------------------------
+    The contents of this file should be added to a AWS  Lambda function 
+    created as part of the EDSA Cloud-Computing Predict. 
+    For further guidance around this process, see the README instruction 
+    file which sits at the root of this repo.
+    ---------------------------------------------------------------------
+
+"""
+
+# Lambda dependencies
+import boto3    # Python AWS SDK
+import json     # Used for handling API-based data.
+import base64   # Needed to decode the incoming POST
+import random
+import uuid
+from botocore.exceptions import ClientError
+
+#CREATE_RAW_PATH = "/contactme"
+
+def lambda_handler(event, context):
+    if event["rawPath"]== "/contactme":
+        # Perform JSON data decoding 
+        body_enc = json.loads(event['body'])
+        body_enc = event['body']
+        dec_dict = json.loads(base64.b64decode(body_enc))
+    
+    table.put_item(Item={'ResponsesID': rid, # <--- Insert the correct variable
+                        'Name': dec_dict['name'], # <--- Insert the correct variable
+                        'Email': dec_dict['email'], # <--- Insert the correct variable
+                        'Cell': dec_dict['phone'], # <--- Insert the correct variable
+                        'Message': dec_dict['message'] # <--- Insert the correct variable
+    })
+    
+    # --- Write to dynamodb ---
+    
+    # ** Create a variable that can take a random value between 1 and 1 000 000 000. 
+    # This variable will be used as our key value i.e the ResponsesID and should be of type integer.
+    # It is important to note that the ResponseID i.e. the rid variable, should take
+    # on a unique value to prevent errors when writing to DynamoDB. **
+    
+    # --- Insert your code here ---
+    rid =random.randint(1,1000000)
+   # rid = None # <--- Replace this value with your code.
+    # -----------------------------
+    
+    # ** Instantiate the DynamoDB service with the help of the boto3 library **
+    
+    # --- Insert your code here ---
+    dynamodb = boto3.resource('dynamodb')#,region_name='eu-west-1') # <--- Replace this value with your code.
+    # -----------------------------
+    
+    # Instantiate the table. Remember pass the name of the DynamoDB table created in step 4
+    table = dynamodb.Table('PredictDB')
+    
+    # ** Write the responses to the table using the put_item method. **
+
+    # Complete the below code so that the appropriate 
+    # incoming data is sent to the matching column in your DynamoDB table
+    # --- Insert your code here ---
+    """db_response = table.put_item(Item={'ResponsesID': rid, # <--- Insert the correct variable
+                        'Name': dec_dict['name'], # <--- Insert the correct variable
+                        'Email': dec_dict['email'], # <--- Insert the correct variable
+                        'Cell': dec_dict['phone'], # <--- Insert the correct variable
+                        'Message': dec_dict['message'] # <--- Insert the correct variable
+    })
+    # -----------------------------
+    """
+    #email_text = 'Hello world'
+
+    # ** SES Functionality **
+
+    # Replace sender@example.com with your "From" address.
+    # This address must be verified with Amazon SES.
+    # --- Insert your code here ---
+    """"SENDER = 'ntseleta@gmail.com'
+    ses.send_mail(
+        Source='ntseleta@gmail.com',
+        Destination={
+            'ToAddresses': [
+                'ntselet@hotmail.com',
+            ]
+        },
+        Message={
+            'Subject': {
+                'Data': 'Predict',
+                'Charset': 'UTF-8'
+            },
+            'Body': {
+                'Text': {
+                    'Data': email_text,
+                    'Charset': 'UTF-8'
+                },
+
+            }
+        },
+    )
+    # -----------------------------
+
+    # Replace recipient@example.com with a "To" address. If your account 
+    # is still in the sandbox, this address must be verified.
+    # --- Insert your code here ---
+    RECIPIENT = 'ntseleta@gmail.com'
+    # -----------------------------
+
+    # The subject line for the email.
+    # --- DO NOT MODIFY THIS CODE ---
+    SUBJECT = f"Data Science Portfolio Project Website - Hello {dec_dict['name']}"
+    # -------------------------------
+
+    # The email body for recipients with non-HTML email clients
+    BODY_TEXT = (email_text)
+
+    # The character encoding for the email.
+    CHARSET = "UTF-8"
+
+    # Create a new SES service resource
+    client = boto3.client('ses')
+
+    # Try to send the email.
+    try:
+        # Provide the contents of the email.
+        ses_response = client.send_email(
+            Destination={
+                'ToAddresses': [
+                    RECIPIENT,
+                    # 'edsa.predicts@explore-ai.net', # <--- Uncomment this line once you have successfully tested your predict end-to-end
+                ],
+            },
+            Message={
+                'Body': {
+
+                    'Text': {
+                        'Charset': CHARSET,
+                        'Data': BODY_TEXT,
+                    },
+                },
+                'Subject': {
+                    'Charset': CHARSET,
+                    'Data': SUBJECT,
+                },
+            },
+            Source=SENDER,
+        )
+
+    # Display an error if something goes wrong.	
+    except ClientError as e:
+        print(e.response['Error']['Message'])
+    else:
+        print("Email sent! Message ID:"),
+        print(ses_response['MessageId'])
+
+
+    # ** Create a response object to inform the website 
+    #    that the workflow executed successfully. **
+    lambda_response = {
+        'statusCode': 200,
+        'body': json.dumps({
+        'Name': dec_dict['Name'],
+        'Email': dec_dict['Email'],
+        'Cell': dec_dict['Phone_number'], 
+        'Message': dec_dict['Message'],
+        'DB_response': db_response
+        })
+    }"""
+    
+    return lambda_response
+
+
+
diff --git a/student_solution_files/main.py b/student_solution_files/main.py
new file mode 100644
index 0000000..de9e0e6
--- /dev/null
+++ b/student_solution_files/main.py
@@ -0,0 +1,367 @@
+"""
+    Final AWS Lambda function skeleton.
+
+    Author: Explore Data Science Academy.
+
+    Note:
+    ---------------------------------------------------------------------
+    The contents of this file should be added to a AWS  Lambda function
+    created as part of the EDSA Cloud-Computing Predict.
+    For further guidance around this process, see the README instruction
+    file which sits at the root of this repo.
+    ---------------------------------------------------------------------
+
+"""
+
+# Lambda dependencies
+import boto3  # Python AWS SDK
+import json  # Used for handling API-based data.
+import base64  # Needed to decode the incoming POST data
+import numpy as np  # Array manipulation
+import random
+rid = random
+from botocore.exceptions import ClientError  # Catch errors on client side
+
+
+# <<< You will need to add additional libraries to complete this script >>>
+
+# ** Insert key phrases function **
+def key_phrase_finder(list_of_important_phrases, list_of_extracted_phrases):
+    listing = []
+    PhraseChecker = None
+
+    res = str(list_of_extracted_phrases).split()
+
+    for important_word in list_of_important_phrases:
+        names = res
+        names2 = [word for word in names if important_word in word]
+        isnot_empty = np.array(names2).size > 0
+
+        if isnot_empty == True:
+            listing = np.append(listing, names2)
+
+        else:
+            listing = listing
+
+    if np.array(listing).size > 0:
+        PhraseChecker = True
+
+    else:
+        PhraseChecker = False
+
+        # -----------------------------
+
+        # ** Insert sentiment extraction function **
+
+    def find_max_sentiment(Comprehend_Sentiment_Output):
+
+        sentiment_score = 0
+
+        if Comprehend_Sentiment_Output['Sentiment'] == 'POSITIVE':
+            sentiment_score = Comprehend_Sentiment_Output['SentimentScore']['Positive']
+
+        elif Comprehend_Sentiment_Output['Sentiment'] == 'NEGATIVE':
+            sentiment_score = Comprehend_Sentiment_Output['SentimentScore']['Negative']
+
+        elif Comprehend_Sentiment_Output['Sentiment'] == 'NEUTRAL':
+            sentiment_score = Comprehend_Sentiment_Output['SentimentScore']['Neutral']
+
+        else:
+            sentiment_score = Comprehend_Sentiment_Output['SentimentScore']['Mixed']
+
+        print(sentiment_score, Comprehend_Sentiment_Output['Sentiment'])
+
+        return Comprehend_Sentiment_Output['Sentiment'], sentiment_score
+
+
+# -----------------------------
+
+# ** Insert email responses function **
+def email_response(name, critical_phrase_list, list_of_extracted_phrases, AWS_Comprehend_Sentiment_Dump):
+    # Function Constants
+    SENDER_NAME = 'Thulasizwe'
+
+    # --- Check for the sentiment of the message and find dominant sentiment score ---
+    Sentiment_finder = find_max_sentiment(AWS_Comprehend_Sentiment_Dump)
+    overwhelming_sentiment = Sentiment_finder[0]
+    overwhelming_sentiment_score = Sentiment_finder[1]
+
+    # --- Check for article critical phrases ---
+    Phrase_Matcher_Article = key_phrase_finder(critical_phrase_list, list_of_extracted_phrases)
+    Matched_Phrases_Article = Phrase_Matcher_Article[0]
+    Matched_Phrases_Checker_Article = Phrase_Matcher_Article[1]
+
+    # --- Check for project phrases ---
+    Phrase_Matcher_Project = key_phrase_finder(['github', 'git', 'Git',
+                                                'GitHub', 'projects',
+                                                'portfolio', 'Portfolio'],
+                                               list_of_extracted_phrases)
+    Matched_Phrases_Project = Phrase_Matcher_Project[0]
+    Matched_Phrases_Checker_Project = Phrase_Matcher_Project[1]
+
+    # --- Check for C.V phrases ---
+    Phrase_Matcher_CV = key_phrase_finder(['C.V', 'resume', 'Curriculum Vitae',
+                                           'Resume', 'CV'],
+                                          list_of_extracted_phrases)
+    Matched_Phrases_CV = Phrase_Matcher_CV[0]
+    Matched_Phrases_Checker_CV = Phrase_Matcher_CV[1]
+
+    # --- Generate standard responses ---
+    # === DO NOT MODIFY THIS TEXT FOR THE PURPOSE OF PREDICT ASSESSMENT ===
+    Greetings_text = f'Good day {name},'
+
+    CV_text = 'I see that you mentioned my C.V in your message. \
+               I am happy to forward you my C.V in response. \
+               If you have any other questions or C.V related queries please do get in touch. '
+
+    Project_Text = 'The projects I listed on my site only include \
+                    the ones not running in production. I have \
+                    several other projects that might interest you.'
+
+    Article_Text = 'In your message you mentioned my blog posts and data science articles. \
+                   I have several other articles published in academic journals. \
+                   Please do let me know if you are interested - I am happy to forward them to you'
+
+    Negative_Text = f'I see that you are unhappy in your response. \
+                    Can we please set up a session to discuss why you are not happy, \
+                    be it with the website, my personal projects or anything else. \
+                    \n\nLooking forward to our discussion. \n\nKind Regards, \n\nMy Name'
+
+    Neutral_Text = f'Thank you for your email. Let me know if you need any additional information.\
+                    \n\nKind Regards, \n\n{SENDER_NAME}'
+
+    Farewell_Text = f'Thank you for your email.\n\nIf there is anything else I can assist \
+                     you with please let me know and I will set up a meeting for us to meet\
+                     in person.\n\nKind Regards, \n\n{SENDER_NAME}'
+    # =====================================================================
+
+    # --- Email Logic ---
+    if overwhelming_sentiment == 'POSITIVE':
+        if ((Matched_Phrases_Checker_CV == True) & \
+                (Matched_Phrases_Checker_Article == True) & \
+                (Matched_Phrases_Checker_Project == True)):
+
+            mytuple = (Greetings_text, CV_text, Article_Text, Project_Text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+        elif ((Matched_Phrases_Checker_CV == True) & \
+              (Matched_Phrases_Checker_Article == False) & \
+              (Matched_Phrases_Checker_Project == True)):
+
+            mytuple = (Greetings_text, CV_text, Project_Text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+        elif ((Matched_Phrases_Checker_CV == True) & \
+              (Matched_Phrases_Checker_Article == False) & \
+              (Matched_Phrases_Checker_Project == False)):
+
+            mytuple = (Greetings_text, CV_text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+        elif ((Matched_Phrases_Checker_CV == False) & \
+              (Matched_Phrases_Checker_Article == True) & \
+              (Matched_Phrases_Checker_Project == False)):
+
+            mytuple = (Greetings_text, Article_Text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+        elif ((Matched_Phrases_Checker_CV == False) & \
+              (Matched_Phrases_Checker_Article == False) & \
+              (Matched_Phrases_Checker_Project == False)):
+
+            mytuple = (Greetings_text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+        elif ((Matched_Phrases_Checker_CV == False) & \
+              (Matched_Phrases_Checker_Article == False) & \
+              (Matched_Phrases_Checker_Project == True)):
+
+            mytuple = (Greetings_text, Project_Text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+        elif ((Matched_Phrases_Checker_CV == True) & \
+              (Matched_Phrases_Checker_Article == True) & \
+              (Matched_Phrases_Checker_Project == False)):
+
+            mytuple = (Greetings_text, CV_text, Article_Text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+        else:
+            mytuple = (Greetings_text, Project_Text, Article_Text, Farewell_Text)
+            Text = "\n \n".join(mytuple)
+
+    elif overwhelming_sentiment == 'NEGATIVE':
+        mytuple = (Greetings_text, Negative_Text)
+        Text = "\n \n".join(mytuple)
+
+    else:
+        mytuple = (Greetings_text, Neutral_Text)
+        Text = "\n \n".join(mytuple)
+
+    return Text
+
+
+# -----------------------------
+
+# Lambda function orchestrating the entire predict logic
+def lambda_handler(event, context):
+    # Perform JSON data decoding
+    body_enc = event['body']
+    dec_dict = json.loads(base64.b64decode(body_enc))
+
+    # ** Insert code to write to dynamodb **
+    # <<< Ensure that the DynamoDB write response object is saved
+    #    as the variable `db_response` >>>
+    rid = np.random.randint(1, 1000000000)  # <--- Replace this value with your code.
+    # -----------------------------
+
+    # ** Instantiate the DynamoDB service with the help of the boto3 library **
+
+    # --- Insert your code here ---
+    dynamodb = boto3.resource('dynamodb', region_name='eu-west-1')  # <--- Replace this value with your code.
+    # -----------------------------
+
+    # Instantiate the table. Remember pass the name of the DynamoDB table created in step 4
+    table = dynamodb.Table('PredictDB')
+
+    # Do not change the name of this variable
+    db_response = table.put_item(Item={'ResponsesID': rid,  # <--- Insert the correct variable
+                                       'Name': dec_dict['name'],  # <--- Insert the correct variable
+                                       'Email': dec_dict['email'],  # <--- Insert the correct variable
+                                       'Cell': dec_dict['phone'],  # <--- Insert the correct variable
+                                       'Message': dec_dict['message']  # <--- Insert the correct variable
+                                       })
+    # -----------------------------
+
+    # --- Amazon Comprehend ---
+    comprehend = boto3.client(service_name='comprehend')
+
+    # --- Insert your code here ---
+    enquiry_text = client.batch_detect_dominant_language(
+        TextList=[
+            'Thank you line 243',
+        ]
+    )  # <--- Insert code to place the website message into this variable
+    # -----------------------------
+
+    # --- Insert your code here ---
+    sentiment = comprehend.detect_sentiment(
+        Text=dec_dict[‘message’], LanguageCode = 'en')  # <---Insert code to get the sentiment with AWS comprehend
+    # -----------------------------
+
+    # --- Insert your code here ---
+    key_phrases = key_phrases = comprehend.detect_key_phrases(Text=comments, LanguageCode='en')
+    key_phrases = comprehend.detect_key_phrases(Text=comments, LanguageCode='en')
+    # <--- Insert code to get the key phrases with AWS comprehend
+    # -----------------------------
+
+    # Get list of phrases in numpy array
+    phrase = []
+    for i in range(0, len(key_phrases['KeyPhrases']) - 1):
+        phrase = np.append(phrase, key_phrases['KeyPhrases'][i]['Text'])
+
+    # ** Use the `email_response` function to generate the text for your email response **
+    # <<< Ensure that the response text is stored in the variable `email_text` >>>
+    # --- Insert your code here ---
+    # Do not change the name of this variable
+    email_text = 'Hello there! Thank you for your message'
+
+    # -----------------------------
+
+    # ** SES Functionality **
+
+    # Insert code to send an email, using AWS SES, with the above defined
+    # `email_text` variable as it's body.
+    # <<< Ensure that the SES service response is stored in the variable `ses_response` >>>
+    # --- Insert your code here ---
+    SENDER = 'ntselet@hotmail.com'
+    # -----------------------------
+
+    # Replace recipient@example.com with a "To" address. If your account
+    # is still in the sandbox, this address must be verified.
+    # --- Insert your code here ---
+    RECIPIENT = 'ntselet@gmail.com'
+    # -----------------------------
+
+    AWS_REGION = "eu-west-1"
+
+    # The subject line for the email.
+    # --- DO NOT MODIFY THIS CODE ---
+    SUBJECT = f"Data Science Portfolio Project Website - Hello {dec_dict['name']}"
+    # -------------------------------
+
+    # The email body for recipients with non-HTML email clients
+    BODY_TEXT = (email_text)
+
+    # The character encoding for the email.
+    CHARSET = "UTF-8"
+
+    # Create a new SES service resource
+    client = boto3.client('ses', region_name='eu-west-1')
+
+    # Do not change the name of this variable
+    # ses_response = None
+    try:
+        # Provide the contents of the email.
+        ses_response = client.send_email(
+            Destination={
+                'ToAddresses': [
+                    RECIPIENT, 'ntseleta@gmail.com'
+                    # 'edsa.predicts@explore-ai.net', # <--- Uncomment this line once you have successfully tested your predict end-to-end
+                ],
+            },
+            Message={
+                'Body': {
+
+                    'Text': {
+                        'Charset': CHARSET,
+                        'Data': BODY_TEXT,
+                    },
+                },
+                'Subject': {
+                    'Charset': CHARSET,
+                    'Data': SUBJECT,
+                },
+            },
+            Source=SENDER,
+
+        )
+
+# Display an error if something goes wrong.
+except ClientError as e:
+print(e.response['Error']['Message'])
+else:
+print("Email sent! Message ID:"),
+print(ses_response['MessageId'])
+
+# ...
+
+# Do not modify the email subject line
+SUBJECT = f"Data Science Portfolio Project Website - Hello {dec_dict['name']}"
+
+# -----------------------------
+
+
+# ** Create a response object to inform the website that the
+#    workflow executed successfully. Note that this object is
+#    used during predict marking and should not be modified.**
+# --- DO NOT MODIFY THIS CODE ---
+lambda_response = {
+    'statusCode': 200,
+    'body': json.dumps({
+        'Name': dec_dict['name'],
+        'Email': dec_dict['email'],
+        'Cell': dec_dict['phone'],
+        'Message': dec_dict['message'],
+        'DB_response': db_response,
+        'SES_response': ses_response,
+    'Email_message': email_text
+    })
+}
+# -----------------------------
+
+return lambda_response
+
+"""
+Your module description
+"""
diff --git a/student_solution_files/predict_detail_submission_template.csv b/student_solution_files/predict_detail_submission_template.csv
index 8c70fbe..d400973 100644
--- a/student_solution_files/predict_detail_submission_template.csv
+++ b/student_solution_files/predict_detail_submission_template.csv
@@ -1,2 +1,2 @@
 Name,Surname,Website_URL,API_Gateway_URL
-Dorah,Explorer,https://sample-website-url.com,https://sample-api-url.com
\ No newline at end of file
+Thulasizwe,Ntsele,https://predict.d3n2uqpd60ztr.amplifyapp.com/,https://98005irfla.execute-api.eu-west-1.amazonaws.com/rootfunction
\ No newline at end of file
diff --git a/student_solution_files/step7.py b/student_solution_files/step7.py
new file mode 100644
index 0000000..a9f0e0a
--- /dev/null
+++ b/student_solution_files/step7.py
@@ -0,0 +1,162 @@
+"""
+    Initial AWS Lambda function is used to decode POST-request data received from the 
+    student portfolio website.
+    
+    Author: Explore Data Science Academy.
+    Note:
+    ---------------------------------------------------------------------
+    The contents of this file should be added to a AWS  Lambda function 
+    created as part of the EDSA Cloud-Computing Predict. 
+    For further guidance around this process, see the README instruction 
+    file which sits at the root of this repo.
+    ---------------------------------------------------------------------
+"""
+
+# Lambda dependencies
+import boto3    # Python AWS SDK
+import json     # Used for handling API-based data.
+import base64   # Needed to decode the incoming POST data
+import random   #Used to generate random numbers
+from botocore.exceptions import ClientError # Catch errors on client side
+import numpy as np #array manipulation
+
+def lambda_handler(event, context):
+    
+    # Perform JSON data decoding 
+    body_enc = json.loads(event['body'])
+    #body_enc = event['body']
+    dec_dict = json.loads(base64.b64decode(body_enc))
+
+    # Note that all of the POST data from our website form can now 
+    # be accessed via the `dec_dict` dictionary object. 
+    # For example, if we entered the name field as 'Student_name on the website' :
+    # >>> dec_dict['name']
+    # 'Student_name'
+    
+    # Create a response object to tell the website that the form data 
+    # was successfully received. We use the contents of the decoded JSON dictionary
+    # to create this response. As the predict progresses, we'll include 
+    # more information about the AWS services we will invoke. 
+
+
+# --- Write to dynamodb ---
+    
+    # ** Create a variable that can take a random value between 1 and 1 000 000 000. 
+    # This variable will be used as our key value i.e the ResponsesID and should be of type integer.
+    # It is important to note that the ResponseID i.e. the rid variable, should take
+    # on a unique value to prevent errors when writing to DynamoDB. **
+    
+    # --- Insert your code here ---
+    rid = np.random.randint(1,1000000000) # <--- Replace this value with your code.
+    # -----------------------------
+    
+    # ** Instantiate the DynamoDB service with the help of the boto3 library **
+    
+    # --- Insert your code here ---
+    dynamodb = boto3.resource('dynamodb', region_name='eu-west-1') # <--- Replace this value with your code.
+    # -----------------------------
+    
+    # Instantiate the table. Remember pass the name of the DynamoDB table created in step 4
+    table = dynamodb.Table('PredictDB')
+    
+    # ** Write the responses to the table using the put_item method. **
+
+    # Complete the below code so that the appropriate 
+    # incoming data is sent to the matching column in your DynamoDB table
+    # --- Insert your code here ---
+    db_response = table.put_item(Item={'ResponsesID': rid, # <--- Insert the correct variable
+                        'Name': dec_dict['name'], # <--- Insert the correct variable
+                        'Email': dec_dict['email'], # <--- Insert the correct variable
+                       'Cell': dec_dict['phone'], # <--- Insert the correct variable
+                        'Message': dec_dict['message'] # <--- Insert the correct variable
+    })
+    # -----------------------------
+
+    # ** Create a response object to inform the website 
+    #    that the workflow executed successfully. **
+    
+    email_text = 'Hello there! Thank you for your message'
+    
+     # ** SES Functionality **
+
+    # Replace sender@example.com with your "From" address.
+    # This address must be verified with Amazon SES.
+    # --- Insert your code here ---
+    SENDER = 'ntselet@hotmail.com'
+    # -----------------------------
+
+    # Replace recipient@example.com with a "To" address. If your account 
+    # is still in the sandbox, this address must be verified.
+    # --- Insert your code here ---
+    RECIPIENT = 'ntselet@gmail.com' 
+    # -----------------------------
+
+    AWS_REGION = "eu-west-1"
+
+    # The subject line for the email.
+    # --- DO NOT MODIFY THIS CODE ---
+    SUBJECT = f"Data Science Portfolio Project Website - Hello {dec_dict['name']}"
+    # -------------------------------
+
+    # The email body for recipients with non-HTML email clients
+    BODY_TEXT = (email_text)
+
+    # The character encoding for the email.
+    CHARSET = "UTF-8"
+
+    
+    # Create a new SES service resource
+    client = boto3.client('ses',region_name=AWS_REGION)
+    
+    
+    # Try to send the email.
+    try:
+        #Provide the contents of the email.
+        ses_response = client.send_email(
+            Destination={
+                'ToAddresses': [
+                    RECIPIENT,
+                    # 'edsa.predicts@explore-ai.net', # <--- Uncomment this line once you have successfully tested your predict end-to-end
+                ],
+            },
+            Message={
+                'Body': {
+
+                    'Text': {
+                        'Charset': CHARSET,
+                        'Data': BODY_TEXT,
+                    },
+                },
+                'Subject': {
+                    'Charset': CHARSET,
+                    'Data': SUBJECT,
+                },
+            },
+            Source=SENDER,
+            
+        )
+
+    # Display an error if something goes wrong.	
+    except ClientError as e:
+        print(e.response['Error']['Message'])
+    else:
+        print("Email sent! Message ID:"),
+        print(ses_response['MessageId'])
+
+    # ** Create a response object to inform the website 
+    #    that the workflow executed successfully. **
+      
+    lambda_response = {
+        'statusCode': 200,
+        'body': json.dumps({
+        'Name': dec_dict['name'],
+        'Email': dec_dict['email'],
+        'Cell': dec_dict['phone'], 
+        'Message': dec_dict['message'],
+        'SES_response': ses_response,
+        'Email_message': email_text,
+        'DB_response': db_response
+        })
+    }
+    
+    return lambda_response