diff --git a/python/src/main.cpp b/python/src/main.cpp
index 59d16ab..5800914 100644
--- a/python/src/main.cpp
+++ b/python/src/main.cpp
@@ -39,10 +39,14 @@ PYBIND11_MODULE(kp, m) {
                 return std::unique_ptr<kp::Tensor>(new kp::Tensor(data, tensorTypes));
             }), "Initialiser with list of data components and tensor GPU memory type.")
         .def("data", &kp::Tensor::data, DOC(kp, Tensor, data))
+        .def("get", [](kp::Tensor &self, uint32_t index) -> float { return self.data()[index]; },
+                "When only an index is necessary")
+        .def("set", [](kp::Tensor &self, uint32_t index, float value) {
+                self.data()[index] = value; })
+        .def("set", &kp::Tensor::setData, "Overrides the data in the local Tensor memory.")
         .def("size", &kp::Tensor::size, "Retrieves the size of the Tensor data as per the local Tensor memory.")
         .def("tensor_type", &kp::Tensor::tensorType, "Retreves the memory type of the tensor.")
         .def("is_init", &kp::Tensor::isInit, "Checks whether the tensor GPU memory has been initialised.")
-        .def("set_data", &kp::Tensor::setData, "Overrides the data in the local Tensor memory.")
         .def("map_data_from_host", &kp::Tensor::mapDataFromHostMemory, "Maps data into GPU memory from tensor local data.")
         .def("map_data_into_host", &kp::Tensor::mapDataIntoHostMemory, "Maps data from GPU memory into tensor local data.");
 
@@ -74,12 +78,12 @@ PYBIND11_MODULE(kp, m) {
             "Records an operation using a custom shader provided from a shader path")
         .def("record_algo_data", [](kp::Sequence &self,
                                     std::vector<std::shared_ptr<kp::Tensor>> tensors,
-                                    py::bytes &bytes) {
+                                    py::bytes &bytes) -> float {
                 // Bytes have to be converted into std::vector
                 py::buffer_info info(py::buffer(bytes).request());
                 const char *data = reinterpret_cast<const char *>(info.ptr);
                 size_t length = static_cast<size_t>(info.size);
-                self.record<kp::OpAlgoBase>(
+                return self.record<kp::OpAlgoBase>(
                     tensors,
                     std::vector<char>(data, data + length));
             },
diff --git a/python/test/test_kompute.py b/python/test/test_kompute.py
index 7d201f2..930b8d6 100644
--- a/python/test/test_kompute.py
+++ b/python/test/test_kompute.py
@@ -214,18 +214,10 @@ def test_logistic_regression_pyshader():
         sq.eval()
 
         # Calculate the parameters based on the respective derivatives calculated
-        w_in_i_val = tensor_w_in.data()[0]
-        w_in_j_val = tensor_w_in.data()[1]
-        b_in_val = tensor_b_in.data()[0]
-
         for j_iter in range(tensor_b_out.size()):
-            w_in_i_val -= learning_rate * tensor_w_out_i.data()[j_iter]
-            w_in_j_val -= learning_rate * tensor_w_out_j.data()[j_iter]
-            b_in_val -= learning_rate * tensor_b_out.data()[j_iter]
-
-        # Update the parameters to process inference again
-        tensor_w_in.set_data([w_in_i_val, w_in_j_val])
-        tensor_b_in.set_data([b_in_val])
+            tensor_w_in.set(0, tensor_w_in.get(0) - learning_rate * tensor_w_out_i.data()[j_iter])
+            tensor_w_in.set(1, tensor_w_in.get(1) - learning_rate * tensor_w_out_j.data()[j_iter])
+            tensor_b_in.set(0, tensor_b_in.get(0) - learning_rate * tensor_b_out.data()[j_iter])
 
     assert tensor_w_in.data()[0] < 0.01
     assert tensor_w_in.data()[0] > 0.0