For a more rigorous, scientific and yet still thoroughly digestible talk I strongly recommend watching Dr. Richard Alley's talk "The Biggest Control Knob: Carbon Dioxide in Earth's Climate History" [0]
As a Bayesian I particularly enjoy Alley's running theme that: while there certainly could be alternative explanations for what is happening, we simply cannot find anything that explains the data better than CO2.
I see many skeptics pointing out tiny holes in the main AGW hypotheses, but the real Bayesian test is "how much better does one hypothesis explain the observed data than then other?". When you put all the pieces of the atmospheric CO2 argument together it seem to explain what we're observing dramatically better than a thousand "...but what about?" that don't fit together into a coherent counter hypothesis.
As an example: Suppose I come home and see my front window broken, my door open and my laptop missing. I assume I have been robbed based on this evidence. You could say "but couldn't the window have been broken by some kid throwing rocks?", "maybe you left the door unlocked and the wind blew it open", "are you absolutely sure you didn't leave your laptop at work?"
While individually each of these counter hypotheses may explain a single event just as well, together they don't work:
P(window broke, door open, laptop missing | robbed) x P(robbed) >> P(window broke, door open, laptop missing | neighbor threw rock, left door unlocked and left laptop at work) x P(neighbor threw rock & left door unlocked & left laptop at work).
[0] https://www.youtube.com/watch?v=RffPSrRpq_g
edit: forgot to add my priors in that last section