diff --git a/examples/nvflare/regression-quantile/QuantileRegression/input_quantile/dataset_quantile_test_site1.csv b/examples/nvflare/regression-quantile/QuantileRegression/input_quantile/dataset_quantile_test_site1.csv
new file mode 100644
index 00000000..dface9b0
--- /dev/null
+++ b/examples/nvflare/regression-quantile/QuantileRegression/input_quantile/dataset_quantile_test_site1.csv
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diff --git a/examples/nvflare/regression-quantile/QuantileRegression/input_quantile/dataset_quantile_test_site2.csv b/examples/nvflare/regression-quantile/QuantileRegression/input_quantile/dataset_quantile_test_site2.csv
new file mode 100644
index 00000000..d403ebc6
--- /dev/null
+++ b/examples/nvflare/regression-quantile/QuantileRegression/input_quantile/dataset_quantile_test_site2.csv
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+3.950432395849068,1.7430483874205973,2.948659494172899,0.8587542276712088,10.339679787908228
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+0.1974748416310258,0.9097150336161112,3.782845797845316,0.48906743585420664,6.632791593953098
+-1.167536136606137,0.5508141335799777,2.2709211464204113,0.8216004534436003,5.158118044077412
+1.2407987322246123,2.621144598654749,4.194587933163472,1.1780837104772361,8.655739032371322
+0.3370555426797027,0.933234345704298,2.2225764182092624,0.7625140213286697,6.662389147813401
+2.0454859481291354,0.6459236434457174,3.5520925249296065,0.6367721819499031,10.161875710245637
+-0.7443932768493091,1.1440500766333623,4.2436351816026345,0.4818937559756582,5.811787577133015
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+-0.23334054271125637,1.0631882715663847,2.223147195833903,-0.028041000958458517,4.484980486202364
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+-0.2307804250844785,0.719304377602471,3.948663707552609,1.0604198920606085,7.668907999881689
+-2.006002357176499,1.046340052365555,4.220022666668422,0.39831864837394576,5.440778928814211
+1.2671863977787816,1.7191761149893743,3.6212861453901537,0.6824914198276256,7.782031058607393
+1.429164743201141,1.1627192905713932,2.5347605774694197,0.6203011571089426,8.054411467325968
+2.0342832810515192,0.9797458509101197,3.3776804316176574,0.8739887971993514,10.115418364170566
+1.3463312232131317,1.302597569780293,4.9066439391252334,1.1360865882756106,10.060190258492312
+1.2871728569957797,0.7309907119279477,3.808280945540014,0.5712986447099703,7.941271404562799
+-1.5142024429017304,-0.09432342087640633,4.587198912082222,0.39983079196201127,6.622533547225454
+0.7197318410057648,0.90804825035082,3.7323236967634523,0.5069745381240358,8.410246656655108
+-0.8598689058721194,-0.5932958471264267,1.8597511506391444,1.2886776906035096,8.051479911090576
+0.16509714681124532,1.0413305680503537,2.5966822489643486,1.2940138592122565,7.774287874907411
+2.175943879016436,1.4469270699029377,3.3853305139547745,0.8286059750106926,8.811760555685739
+0.5386633316846006,1.792533635133885,2.068361479199627,0.8862251942343655,6.870831224389158
+-2.6363929259040773,1.517933996661582,3.372348377802427,0.5126570866017395,2.0803061700708803
+-0.7018931562332298,1.2217702381137545,1.2788271056068314,1.0057069059292927,5.861695105713317
+-0.181013207658708,0.5845997152056568,2.762185856639172,0.6259934026487735,7.328863849901206
+0.22921036557530794,0.5407126719376726,3.2940844495582553,0.4471680345185923,6.531056775210318
+1.6256285663637235,1.0739963451023855,1.3369229849201698,0.7764523077282964,7.586711921637442
+1.5041409511165214,0.6809829295779459,3.265249702599067,0.610664546251539,7.536014115595679
+1.4745781703840732,0.6226988864051995,3.5500842400568766,0.7656904171146843,9.040973087407526
+0.7787683677648009,1.2267917076996986,3.575322418186538,0.6921076640321056,7.288672875473288
+0.14587079219766064,0.6889700955560475,1.516736431359612,0.806534685339885,5.61599219055119
+0.0659887946220033,0.10992402585810512,1.6911523304988667,0.7393217566185868,6.980498734177196
+1.0185380895663885,1.0689969179962084,3.7491216717408884,1.2638740642363109,10.17222777156364
+1.6207502570417467,0.6302050316127362,3.7504470037486186,0.9258153149365073,10.208100788669599
+2.363160628052688,1.510538575495708,1.9951501912475815,0.6016412227271656,7.779535953449574
+0.612348088951238,1.976388892403171,1.77812385262072,0.8610217281690593,6.8938199093054395
+0.8537909965086546,1.6560005676339113,3.6163089270826108,0.5266140526808886,7.628124093612748
+2.2825169219189663,1.4618681754504324,1.278864741686384,0.6995351799354955,8.952766769997151
diff --git a/examples/nvflare/regression-quantile/QuantileRegression/model_parameters (1).joblib b/examples/nvflare/regression-quantile/QuantileRegression/model_parameters (1).joblib
new file mode 100644
index 00000000..db8e0d72
Binary files /dev/null and b/examples/nvflare/regression-quantile/QuantileRegression/model_parameters (1).joblib differ
diff --git a/examples/nvflare/regression-quantile/QuantileRegression/results_analize.ipynb b/examples/nvflare/regression-quantile/QuantileRegression/results_analize.ipynb
new file mode 100644
index 00000000..ffcf8bfd
--- /dev/null
+++ b/examples/nvflare/regression-quantile/QuantileRegression/results_analize.ipynb
@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "65470c2b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: joblib in /Users/danieldavid/.pyenv/versions/3.11.6/lib/python3.11/site-packages (1.4.2)\n"
+     ]
+    }
+   ],
+   "source": [
+    "! pip install joblib"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c21f2bf5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model Parameters:\n"
+     ]
+    },
+    {
+     "ename": "AttributeError",
+     "evalue": "'dict' object has no attribute 'get_params'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[2], line 9\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# Analyze the model parameters\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel Parameters:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m----> 9\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m param_name, param_value \u001b[38;5;129;01min\u001b[39;00m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_params\u001b[49m()\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m     10\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparam_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparam_value\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute 'get_params'"
+     ]
+    }
+   ],
+   "source": [
+    "import joblib\n",
+    "\n",
+    "# Load the model parameters from the file\n",
+    "model_file = \"model_parameters (1).joblib\"\n",
+    "model = joblib.load(model_file)\n",
+    "\n",
+    "# Analyze the model parameters\n",
+    "print(\"Model Parameters:\")\n",
+    "for param_name, param_value in model.get_params().items():\n",
+    "    print(f\"{param_name}: {param_value}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5368fb45",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/rhino-sdk/README.md b/examples/rhino-sdk/README.md
index 02d18951..3dea9a05 100644
--- a/examples/rhino-sdk/README.md
+++ b/examples/rhino-sdk/README.md
@@ -1,9 +1,13 @@
 # Rhino Health Examples - Rhino SDK
-This folder contains examples for interacting with Rhino Health's Federated Computing Platform (FCP) using the Python SDK
+
+This folder contains examples for interacting with Rhino Health's Federated Computing Platform (FCP) using the Python SDK.
+
+Each notebook demonstrates how to use the SDK to authenticate your user session, select a project, and perform a variety of federated analytics or compute tasks.
 <br>
 
 # Table of Contents
-- `aggregate_quantile_example.ipynb` - Demonstrate the Rhino Helath SDK's ability to calculate federated percentiles with differential privacy
+
+- `aggregate_quantile_example.ipynb` - Demonstrates how to calculate federated percentiles with differential privacy using the Rhino Health SDK, including interactive project and dataset selection.
 - `cox.ipynb` - Demostrate calculation of Cox proportional hazard with federated data
 - `eda.ipynb` - Demonstrate usage of the Rhino Health Python SDK for performing Exploratory Data Analysis (EDA) using federated analytics
 - `metrics_examples.ipynb` - Examples of calculating metrics using federated analytics, including mean, odds ratio, chi square test, t-test, one way anova, and 2x2 matrix
@@ -15,4 +19,5 @@ This folder contains examples for interacting with Rhino Health's Federated Comp
 <br><br>
 
 # Getting Help
+
 For additional support, please reach out to [support@rhinohealth.com](mailto:support@rhinohealth.com).
diff --git a/examples/rhino-sdk/aggregate_quantile_example.ipynb b/examples/rhino-sdk/aggregate_quantile_example.ipynb
index e5120f5a..88ff5fb1 100644
--- a/examples/rhino-sdk/aggregate_quantile_example.ipynb
+++ b/examples/rhino-sdk/aggregate_quantile_example.ipynb
@@ -47,6 +47,26 @@
     "print(\"Logged In\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "4d2ea28e",
+   "metadata": {},
+   "source": [
+    "### Run this cell to list all of the projects in your environment:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b2c205a7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "projects = session.project.search_for_projects_by_name(name=\"\")\n",
+    "for p in projects:\n",
+    "    print(p.name)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "ef9cf810",
@@ -63,7 +83,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "project = session.project.get_project_by_name(\"PROJECT_NAME\")"
+    "project = session.project.get_project_by_name(\"PROJECT_NAME\")\n",
+    "if not project:\n",
+    "        raise ValueError(\"Project not found.\")\n",
+    "\n",
+    "print(\"Selected project name:\", project.name)"
    ]
   },
   {
@@ -71,7 +95,37 @@
    "id": "f3d20b5f",
    "metadata": {},
    "source": [
-    "### Load the Datasets you would like to calculate federated percentiles for by placing the Dataset names below\n",
+    "### List your available datasets in your project and then load those you would like to calculate federated percentiles"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3c24ea20",
+   "metadata": {},
+   "source": [
+    "Run this cell to list all of your available datasets in your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4e8fdf6c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "all_datasets = session.dataset.search_for_datasets_by_name(name=\"\")\n",
+    "project_datasets = [d for d in all_datasets if d.project and d.project.uid == project.uid]\n",
+    "\n",
+    "print(f\"\\nDatasets in project '{project.name}':\")\n",
+    "for d in project_datasets:\n",
+    "    print(f\"- {d.name}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5c510924",
+   "metadata": {},
+   "source": [
     "Replace `DATASET_1` & `DATASET_2` with the name of your datasets"
    ]
   },
diff --git a/examples/rhino-sdk/cox/README.md b/examples/rhino-sdk/cox/README.md
new file mode 100644
index 00000000..46d27bfa
--- /dev/null
+++ b/examples/rhino-sdk/cox/README.md
@@ -0,0 +1,22 @@
+## This folder contains a minimal working example for computing Cox proportional hazard metrics using the Rhino SDK.
+
+## Files
+
+- `cox_sampledata1.csv` – sample dataset 1
+- `cox_sampledata2.csv` – sample dataset 2
+- `cox.ipynb` – interactive notebook demonstrating the end-to-end process
+
+## How to Use
+
+1. Upload both CSV files as datasets in your Rhino project.
+2. Run the cells in `cox.ipynb` to compute and visualize the Cox regression results.
+3. All column names are pre-formatted and aligned with the metric's expected input schema.
+
+### Both sample datasets are synthetic and contain the following columns:
+
+| Column  | Description                         |
+| ------- | ----------------------------------- |
+| `Time`  | Duration until event or censoring   |
+| `Event` | 1 if event occurred / 0 if censored |
+| `COV1`  | Age                                 |
+| `COV2`  | Heart rate                          |
diff --git a/examples/rhino-sdk/cox.ipynb b/examples/rhino-sdk/cox/cox.ipynb
similarity index 68%
rename from examples/rhino-sdk/cox.ipynb
rename to examples/rhino-sdk/cox/cox.ipynb
index cc877dd0..10ee447b 100644
--- a/examples/rhino-sdk/cox.ipynb
+++ b/examples/rhino-sdk/cox/cox.ipynb
@@ -47,6 +47,26 @@
     "print(\"Logged In\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "3e356ff1",
+   "metadata": {},
+   "source": [
+    "### Run this cell to list all of the projects in your environment:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "be154d17",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "projects = session.project.search_for_projects_by_name(name=\"\")\n",
+    "for p in projects:\n",
+    "    print(p.name)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "ef9cf810",
@@ -63,7 +83,42 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "project = session.project.get_project_by_name(\"PROJECT_NAME\")"
+    "project = session.project.get_project_by_name(\"PROJECT_NAME\")\n",
+    "if not project:\n",
+    "        raise ValueError(\"Project not found.\")\n",
+    "\n",
+    "print(\"Selected project name:\", project.name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79293714",
+   "metadata": {},
+   "source": [
+    "### List your available datasets in your project and then load those you would like to calculate federated percentiles"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da386545",
+   "metadata": {},
+   "source": [
+    "Run this cell to list all of your available datasets in your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2c6dc75",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "all_datasets = session.dataset.search_for_datasets_by_name(name=\"\")\n",
+    "project_datasets = [d for d in all_datasets if d.project and d.project.uid == project.uid]\n",
+    "\n",
+    "print(f\"\\nDatasets in project '{project.name}':\")\n",
+    "for d in project_datasets:\n",
+    "    print(f\"- {d.name}\")"
    ]
   },
   {
@@ -111,6 +166,18 @@
     "})"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "bae5e06b",
+   "metadata": {},
+   "source": [
+    "`Time`: The time-to-event or censoring,\n",
+    "\n",
+    "`Event`: The event indicator (1 if the event occurred, 0 if censored),\n",
+    "\n",
+    "`COV1` and `COV2`: are the Covariates that may influence the time-to-event."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -133,7 +200,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -146,7 +213,8 @@
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3"
+   "pygments_lexer": "ipython3",
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,
diff --git a/examples/rhino-sdk/cox/cox_sampledata1.csv b/examples/rhino-sdk/cox/cox_sampledata1.csv
new file mode 100644
index 00000000..9129ec4b
--- /dev/null
+++ b/examples/rhino-sdk/cox/cox_sampledata1.csv
@@ -0,0 +1,21 @@
+Time,Event,COV1,COV2
+56,1,76,85
+97,1,80,103
+19,0,73,93
+76,0,84,69
+65,1,81,95
+25,1,86,73
+87,1,32,90
+91,0,66,107
+79,1,80,74
+79,0,36,67
+92,0,50,73
+28,0,38,82
+7,0,68,119
+26,0,47,116
+57,1,33,99
+6,1,54,80
+92,1,89,75
+34,1,43,104
+42,1,79,77
+6,0,87,106
\ No newline at end of file
diff --git a/examples/rhino-sdk/cox/cox_sampledata2.csv b/examples/rhino-sdk/cox/cox_sampledata2.csv
new file mode 100644
index 00000000..5b6b8797
--- /dev/null
+++ b/examples/rhino-sdk/cox/cox_sampledata2.csv
@@ -0,0 +1,21 @@
+Time,Event,COV1,COV2
+67,0,83,83
+99,1,67,111
+87,1,72,98
+99,1,58,71
+81,0,61,63
+72,0,82,119
+88,1,61,90
+17,1,39,64
+37,1,35,87
+27,1,51,106
+15,1,82,60
+83,0,58,96
+45,1,47,117
+28,0,85,72
+89,0,67,81
+21,0,82,101
+69,0,86,110
+8,0,37,60
+30,1,68,60
+22,1,70,73
\ No newline at end of file
diff --git a/examples/rhino-sdk/eda.ipynb b/examples/rhino-sdk/eda.ipynb
index b19f0b15..d42b9734 100644
--- a/examples/rhino-sdk/eda.ipynb
+++ b/examples/rhino-sdk/eda.ipynb
@@ -28,7 +28,7 @@
    "outputs": [],
    "source": [
     "from getpass import getpass\n",
-    "import rhino_health"
+    "import rhino_health as rh"
    ]
   },
   {
@@ -44,6 +44,80 @@
     "print(\"Logged In\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "8081822f",
+   "metadata": {},
+   "source": [
+    "### Run this cell to list all of the projects in your environment:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3e5a1af0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "projects = session.project.search_for_projects_by_name(name=\"\")\n",
+    "for p in projects:\n",
+    "    print(p.name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c10c0fea",
+   "metadata": {},
+   "source": [
+    "### Load the Project you would like to calculate the metric for by placing the Project's name below\n",
+    "Replace `PROJECT_NAME` with the name of your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b91bff14",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "project = session.project.get_project_by_name(\"PROJECT_NAME\")\n",
+    "if not project:\n",
+    "        raise ValueError(\"Project not found.\")\n",
+    "\n",
+    "print(\"Selected project name:\", project.name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d689f6df",
+   "metadata": {},
+   "source": [
+    "### List your available datasets in your project and then load those you would like to calculate federated percentiles"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97663b1a",
+   "metadata": {},
+   "source": [
+    "Run this cell to list all of your available datasets in your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d32c6d82",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "all_datasets = session.dataset.search_for_datasets_by_name(name=\"\")\n",
+    "project_datasets = [d for d in all_datasets if d.project and d.project.uid == project.uid]\n",
+    "\n",
+    "print(f\"\\nDatasets in project '{project.name}':\")\n",
+    "for d in project_datasets:\n",
+    "    print(f\"- {d.name} : {d.uid}\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -51,10 +125,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "FIRST_TEST_DATASET_ID = \"XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\"  # Replace this\n",
-    "SECOND_TEST_DATASET_ID = \"XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\"  # Replace this\n",
-    "first_dataset = session.dataset.get_dataset(FIRST_TEST_DATASET_ID)\n",
-    "second_dataset = session.dataset.get_dataset(SECOND_TEST_DATASET_ID)\n",
+    "FIRST_TEST_DATASET_UID = \"XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\"   # Replace this with the ID of the first test dataset\n",
+    "SECOND_TEST_DATASET_UID = \"XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\"   # Replace this with the ID of the second test dataset\n",
+    "first_dataset = session.dataset.get_dataset(FIRST_TEST_DATASET_UID)\n",
+    "second_dataset = session.dataset.get_dataset(SECOND_TEST_DATASET_UID)\n",
     "all_datasets = [first_dataset.uid, second_dataset.uid]"
    ]
   },
@@ -146,8 +220,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(\"Grouped Height mean per site\")\n",
-    "\n",
     "mean_verification = Mean(\n",
     "    variable=\"Height\",\n",
     "    group_by={\"groupings\": [\"Gender\"]},\n",
@@ -166,30 +238,57 @@
    "metadata": {},
    "source": [
     "### Calculate Aggregated Metrics Across Multiple Sites\n",
-    "Similarly - all calculations are performed on-prem - only aggregate data returned to the notebook"
+    "Similarly - all calculations are performed on-prem - only aggregate data returned to the notebook.\n",
+    "\n",
+    "This ensures data privacy is preserved at each site while enabling secure federated analysis.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1523904e",
+   "metadata": {},
+   "source": [
+    "#### Aggregate Grouped Height Mean"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3b3a7446",
+   "id": "abca0901",
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(\"Aggregate Grouped Height mean\")\n",
-    "grouped_results = session.project.aggregate_dataset_metric(all_datasets, mean_verification)\n",
+    "print(\"Aggregate Grouped Height Mean:\")\n",
+    "\n",
+    "mean_verification = Mean(\n",
+    "    variable=\"Height\",\n",
+    "    group_by={\"groupings\": [\"Gender\"]}\n",
+    ")\n",
+    "\n",
+    "grouped_results = session.project.aggregate_dataset_metric(\n",
+    "    dataset_uids=[str(first_dataset.uid), str(second_dataset.uid)],\n",
+    "    metric_configuration=mean_verification\n",
+    ")\n",
     "\n",
     "print(f\"{grouped_results.output}\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "8c447e40",
+   "metadata": {},
+   "source": [
+    "#### Complex Aggregation (Filter + Grouping)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0ff603ac",
+   "id": "daf5cc04",
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(\"Complex Aggregation\")\n",
+    "print(\"Complex Aggregation (Filtered and Grouped):\")\n",
     "\n",
     "configuration = Mean(\n",
     "    variable={\n",
@@ -201,18 +300,30 @@
     "    group_by={\"groupings\": [\"Gender\"]}\n",
     ")\n",
     "\n",
-    "grouped_results = session.project.aggregate_dataset_metric(all_datasets, configuration)\n",
-    "print(f\"{grouped_results.output}\")\n"
+    "grouped_results = session.project.aggregate_dataset_metric(\n",
+    "    dataset_uids=[str(first_dataset.uid), str(second_dataset.uid)],\n",
+    "    metric_configuration=configuration\n",
+    ")\n",
+    "\n",
+    "print(f\"{grouped_results.output}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ecff141d",
+   "metadata": {},
+   "source": [
+    "#### Complex Aggregation with Complex Filtering"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4178271b",
+   "id": "75ac907d",
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(\"Complex Aggregation with Complex Filtering\")\n",
+    "print(\"Complex Aggregation with Complex Filtering:\")\n",
     "\n",
     "configuration = Mean(\n",
     "    variable={\n",
@@ -227,33 +338,45 @@
     "    group_by={\"groupings\": [\"Gender\"]}\n",
     ")\n",
     "\n",
-    "grouped_results = session.project.aggregate_dataset_metric(all_datasets, configuration)\n",
+    "grouped_results = session.project.aggregate_dataset_metric(\n",
+    "    dataset_uids=[str(first_dataset.uid), str(second_dataset.uid)],\n",
+    "    metric_configuration=configuration\n",
+    ")\n",
+    "\n",
     "print(f\"{grouped_results.output}\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "80fef651",
+   "metadata": {},
+   "source": [
+    "#### Standard Deviation of Height (Per Site, Not Federated)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f0b5387e",
+   "id": "1e9f2c18",
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(\"Standard Deviation of Height\")\n",
+    "print(\"Standard Deviation of Height (per site, not aggregated):\")\n",
+    "\n",
+    "configuration = StandardDeviation(variable=\"Height\")\n",
     "\n",
-    "configuration = StandardDeviation(\n",
-    "    variable=\"Height\"\n",
-    ")\n",
     "individual_results = {\n",
     "    \"site1\": session.dataset.get_dataset_metric(first_dataset.uid, configuration).output,\n",
     "    \"site2\": session.dataset.get_dataset_metric(second_dataset.uid, configuration).output,\n",
     "}\n",
+    "\n",
     "print(f\"{individual_results}\")"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -267,7 +390,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.4"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,
diff --git a/examples/rhino-sdk/metrics_examples.ipynb b/examples/rhino-sdk/metrics_examples/metrics_examples.ipynb
similarity index 100%
rename from examples/rhino-sdk/metrics_examples.ipynb
rename to examples/rhino-sdk/metrics_examples/metrics_examples.ipynb
diff --git a/examples/rhino-sdk/metrics_examples/metrics_sample_dataset1.csv b/examples/rhino-sdk/metrics_examples/metrics_sample_dataset1.csv
new file mode 100644
index 00000000..e72c0718
--- /dev/null
+++ b/examples/rhino-sdk/metrics_examples/metrics_sample_dataset1.csv
@@ -0,0 +1,27 @@
+Weight,Pneumonia,Smoking,Inflammation Level,Sp02 Level
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
diff --git a/examples/rhino-sdk/metrics_examples/metrics_sample_dataset2.csv b/examples/rhino-sdk/metrics_examples/metrics_sample_dataset2.csv
new file mode 100644
index 00000000..33e5dcc9
--- /dev/null
+++ b/examples/rhino-sdk/metrics_examples/metrics_sample_dataset2.csv
@@ -0,0 +1,30 @@
+Weight,Pneumonia,Smoking,Inflammation Level,Sp02 Level
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
+97.0,True,True,High,0.3
+84.0,True,False,Low,0.3
+97.0,True,True,Medium,0.51
+91.0,True,False,Medium,0.12
+90.0,False,False,High,0.03
+124.0,False,True,High,0.413
diff --git a/examples/rhino-sdk/sql-data-ingestion.ipynb b/examples/rhino-sdk/sql-data-ingestion.ipynb
index 8dc99b49..073c4d5d 100644
--- a/examples/rhino-sdk/sql-data-ingestion.ipynb
+++ b/examples/rhino-sdk/sql-data-ingestion.ipynb
@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "f9e3e349",
    "metadata": {},
    "outputs": [],
@@ -39,19 +39,30 @@
     "    SQLServerTypes,\n",
     "    ConnectionDetails,\n",
     ")\n",
-    "from rhino_health.lib.metrics import Count, FilterType, Mean, StandardDeviation"
+    "from rhino_health.lib.constants import ApiEnvironment\n",
+    "\n",
+    "from rhino_health.lib.metrics import Count, FilterType, Mean, StandardDeviation\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "3b107de9",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Logging In\n",
+      "Logged In\n"
+     ]
+    }
+   ],
    "source": [
     "print(\"Logging In\")\n",
-    "my_username = \"my_email@example.com\" # Replace this with the email you use to log into Rhino Health\n",
-    "session = rh.login(username=my_username, password=getpass())\n",
+    "my_username = \"daniel.david@rhinohealth.com\" # Replace this with the email you use to log into Rhino Health\n",
+    "session = rh.login(username=my_username, password=getpass(),rhino_api_url= ApiEnvironment.STAGING_AWS_URL)\n",
     "print(\"Logged In\")"
    ]
   },
@@ -283,7 +294,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -297,7 +308,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.4"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,