diff --git a/polars/polars-core/src/datatypes/dtype.rs b/polars/polars-core/src/datatypes/dtype.rs
index 711c21d77d5f0..6bdd57056f0b7 100644
--- a/polars/polars-core/src/datatypes/dtype.rs
+++ b/polars/polars-core/src/datatypes/dtype.rs
@@ -23,7 +23,7 @@ pub enum DataType {
     /// in days (32 bits).
     Date,
     /// A 64-bit date representing the elapsed time since UNIX epoch (1970-01-01)
-    /// in milliseconds (64 bits).
+    /// in the given timeunit (64 bits).
     Datetime(TimeUnit, Option<TimeZone>),
     // 64-bit integer representing difference between times in milliseconds or nanoseconds
     Duration(TimeUnit),
diff --git a/py-polars/polars/internals/dataframe/frame.py b/py-polars/polars/internals/dataframe/frame.py
index 22a408cdb77af..7591a63d44979 100644
--- a/py-polars/polars/internals/dataframe/frame.py
+++ b/py-polars/polars/internals/dataframe/frame.py
@@ -292,7 +292,9 @@ def __init__(
         elif isinstance(data, (Generator, Iterable)) and not isinstance(data, Sized):
             self._df = iterable_to_pydf(data, columns=columns, orient=orient)
         else:
-            raise ValueError("DataFrame constructor not called properly.")
+            raise ValueError(
+                f"DataFrame constructor called with unsupported type; got {type(data)}"
+            )
 
     @classmethod
     def _from_pydf(cls: type[DF], py_df: PyDataFrame) -> DF:
diff --git a/py-polars/polars/internals/series/series.py b/py-polars/polars/internals/series/series.py
index 0d343e8bc468f..d8d1b6f457598 100644
--- a/py-polars/polars/internals/series/series.py
+++ b/py-polars/polars/internals/series/series.py
@@ -55,6 +55,7 @@
 from polars.dependencies import numpy as np
 from polars.dependencies import pandas as pd
 from polars.dependencies import pyarrow as pa
+from polars.exceptions import ShapeError
 from polars.internals.construction import (
     arrow_to_pyseries,
     iterable_to_pyseries,
@@ -194,7 +195,7 @@ class Series:
     def __init__(
         self,
         name: str | ArrayLike | None = None,
-        values: ArrayLike | Sequence[Any] | None = None,
+        values: ArrayLike | None = None,
         dtype: type[DataType] | DataType | None = None,
         strict: bool = True,
         nan_to_null: bool = False,
@@ -268,7 +269,9 @@ def __init__(
                 dtype_if_empty=dtype_if_empty,
             )
         else:
-            raise ValueError(f"Series constructor not called properly. Got {values}.")
+            raise ValueError(
+                f"Series constructor called with unsupported type; got {type(values)}"
+            )
 
     @classmethod
     def _from_pyseries(cls, pyseries: PySeries) -> Series:
@@ -589,6 +592,22 @@ def __rpow__(self, other: Any) -> Series:
             )
         return self.to_frame().select(other ** pli.col(self.name)).to_series()
 
+    def __matmul__(self, other: Any) -> float | Series | None:
+        if isinstance(other, Sequence) or (
+            _NUMPY_TYPE(other) and isinstance(other, np.ndarray)
+        ):
+            other = Series(other)
+        # elif isinstance(other, pli.DataFrame):
+        #     return other.__rmatmul__(self)  # type: ignore[return-value]
+        return self.dot(other)
+
+    def __rmatmul__(self, other: Any) -> float | Series | None:
+        if isinstance(other, Sequence) or (
+            _NUMPY_TYPE(other) and isinstance(other, np.ndarray)
+        ):
+            other = Series(other)
+        return other.dot(self)
+
     def __neg__(self) -> Series:
         return 0 - self
 
@@ -3034,7 +3053,7 @@ def round(self, decimals: int) -> Series:
 
         """
 
-    def dot(self, other: Series) -> float | None:
+    def dot(self, other: Series | ArrayLike) -> float | None:
         """
         Compute the dot/inner product between two Series.
 
@@ -3048,9 +3067,14 @@ def dot(self, other: Series) -> float | None:
         Parameters
         ----------
         other
-            Series to compute dot product with
+            Series (or array) to compute dot product with.
 
         """
+        if not isinstance(other, Series):
+            other = Series(other)
+        if len(self) != len(other):
+            n, m = len(self), len(other)
+            raise ShapeError(f"Series length mismatch: expected {n}, found {m}")
         return self._s.dot(other._s)
 
     def mode(self) -> Series:
diff --git a/py-polars/tests/unit/test_series.py b/py-polars/tests/unit/test_series.py
index 108782c8713f4..15527311ba369 100644
--- a/py-polars/tests/unit/test_series.py
+++ b/py-polars/tests/unit/test_series.py
@@ -22,6 +22,7 @@
     UInt32,
     UInt64,
 )
+from polars.exceptions import ShapeError
 from polars.internals.construction import iterable_to_pyseries
 from polars.internals.type_aliases import EpochTimeUnit
 from polars.testing import assert_frame_equal, assert_series_equal
@@ -1613,9 +1614,21 @@ def test_is_duplicated() -> None:
 
 
 def test_dot() -> None:
-    s = pl.Series("a", [1, 2, 3])
+    s1 = pl.Series("a", [1, 2, 3])
     s2 = pl.Series("b", [4.0, 5.0, 6.0])
-    assert s.dot(s2) == 32
+
+    assert np.array([1, 2, 3]) @ np.array([4, 5, 6]) == 32
+
+    for dot_result in (
+        s1.dot(s2),
+        s1 @ s2,
+        [1, 2, 3] @ s2,
+        s1 @ np.array([4, 5, 6]),
+    ):
+        assert dot_result == 32
+
+    with pytest.raises(ShapeError, match="length mismatch"):
+        s1 @ [4, 5, 6, 7, 8]
 
 
 def test_sample() -> None: