In intelligent manufacturing processes, the dependence of the weld quality on the welder’s skills in manual welding should be minimized. To better control the welding quality, a machine–human cooperative control system was designed in this study, and a skills learning experiment was conducted to correlate the relationship between welding speed and welding current. The obtained skills were then transferred to the control system to control the human welder to achieve the desired welding speed. In addition, to adjust the welding current to control the welding power, the desired full penetration welds were finally obtained. In the present study, full penetration welds with different welding speeds were obtained in a 304 stainless steel pipe having a wall thickness of 2.03 mm and an outside diameter of 113.5 mm using the machine–human cooperative welding process. The back fusion width was 2.3 to 5.5 mm, which met the quality requirements of the weld. This study provides a research direction for effectively solving the problem of the shortage of welders and for helping unskilled welders to produce quality welds, and lays the foundation for developing the next generation of machine–human cooperative intelligent welding system.